Modular Fault Diagnosis Based on Discrete Event Systems

Wireless communication is becoming increasingly popular in factory automation and process control systems, especially when moving components are used. One reason for this growth is the benefits that wireless communication offers, which include lower installation costs than wired networks, less mechanical wear and tear and the ability to provide critical information even about the moving components. Robust and reliable wireless communication solutions must accommodate the demanding and changing conditions of the existing industrial environment, such as the variable number of communication elements, possible interference, a large area for which to provide communication and an organic amount of available battery power. For mobile industrial environments, sensor networks appear to be candidates that can meet many or even all of these requirements. Several types of such communication solutions are available and are in use. This paper focuses on selected wireless networks that can be considered to be enabling technology for the new generation of manufacturing systems.

This paper presents the design of industrial standard mixed-signal transmitter based on economical design aspect. The proposed signal transmitter is used to transmit the standard signals for testing and verifying the functionality of factory automation and process control systems in an industrial environment. The standard 4-20 mA current signal is provided in the designed signal transmitter. Additionally, some standard voltage signals are available to enable the flexibility in practical utilization. The voltage outputs can be transmitted within three ranges including 0-5 V, 0-10 V and 1-5 V. The proposed signal transmitter is designed utilizing an open-source electronics prototyping platform Arduino Nano ATMEGA328P microcontroller. Analog to Digital converter (ADC) ADS1115 is used in the transmitter with 16-bit resolution. Digital to Analog converter (DAC) MCP4922, which is dual channel with 12-bit resolution, is used for providing high accuracy output signal levels together with low noises performance. Furthermore, the current gain is used via the operational amplifier TLC 2272 exhibited rail-to-rail output performance. The main portion of signal transmitter is integrated within a small container that offers a portability of the device for field testing. The proposed industrial standard mixed-signal transmitter is tested to investigate the functionality and performance of the device in various experiments. The experimental results evidently demonstrate the complete designated functionality and satisfactory performance based on the existing conventional signal transmitter with low-cost solution.

This paper is concerned with fault detection and location of discrete event systems (DES) modeled using interpreted Petri nets (IPN). The approach held deals with IPN models in which the marking is partially known. A diagnosis scheme that tracks the DES inputs and outputs is proposed; it allows detecting and locating an unexpected behavior within the DES. The diagnoser handles a monitoring model, expressed also as an IPN, which is computed from the DES model through an induced conservative marking law.

Control theories for discrete event systems modeled as finite state machines have been well developed over the years in addressing various fundamental control issues. However, modeling in finite state machines has long suffered the potential problem of state explosion that renders it unsuitable for many practical applications. In this paper, we propose an approach that appends finite sets of parameters to finite state machines in modeling discrete event systems. We show with an example that many discrete event applications can then be represented efficiently in this approach and the state explosion problem can then been mitigated.

Although Finite-State Automata (FSA) have been successfully used in modeling and control of Discrete Event Systems (DESs), they are limited to represent complex and advanced features of DESs, such as context recognition and switching. The literature has suggested that a FSA can nevertheless be enriched with parameters properly collected from the modeled system, so that this favors design and control. A parameter can be embedded either on transitions or states. However, each approach is structured within a specific framework, so that their comparison and integration are not straightforward and they may lead to different control solutions, modeled, computed and implemented using distinct strategies. In this paper, we show how to combine advantages from parameters in modeling and control of DESs. Each approach is structured and their advantages are identified and exemplified. Then, we propose a conversion method that allows to translate a design-friendly model into a synthesis-efficient structure. Examples illustrate the approach.

In order to make it possible to effectively represent deterministic uncertainties and vagueness as well as the human subjective observation and judgement inherent to many real-world problems, especially those in biomedicine, we introduce, in this paper, fuzzy states and fuzzy events and generalize (crisp) discrete event systems (DES) to fuzzy DES. The largely graph-based current framework of the crisp DES is unsuitable for the expansion, and we have thus reformulated it using state vectors and event transition matrices which can be extended to fuzzy vectors and matrices by allowing their elements to take values between 0 and 1. To measure information related to fuzzy DES, we generalize the crisp DES observability. The new observability allows one to determine whether or not the system output observed is sufficient for decision making. Finally, we extend the optimal control of DES to fuzzy DES. The new fuzzy DES theory is consistent with the existing theory, both at the conceptual and the computation levels, in that the former contains the latter as a special case when the memberships must be either 0 or 1. Numerical examples are provided to illustrate the theoretical development.

This paper aims to introduce a facility operation modeling and simulation mainly based on a discrete event system modeling scheme. Facilities have become so much complex that its operational status cannot be estimated by simple calculations. A facility can consist of a lot of unit process and a lot of transportation between consecutive processes, which may be modelled as a time driven system or an event driven system. However, the transportation between processes can usually be considered as a discrete event system and not a continuous system. Therefore, in macro-scale, a facility operation can be simulated on the basis of a discrete event system modeling if we do not consider how an individual process behaves. This study introduces the current status of the studies on an operation modeling and simulation regarding typical nuclear facilities along with some instances. Also, this paper provides insights about how a discrete event system can be applied to a nuclear facility. These kinds of modeling and simulation are very important because they can contribute to a facility design in terms of an optimal process and an equipment layout, a generic understanding for regulators, stakeholders and operators, a system diagnosis through by comparing measurement data with simulation results and furthermore it can contribute to an efficient operation scheduling.

Many technological, industrial or economical systems are described by discrete event system (DES) models. The decision making processes that arise in the design and operation of this kind of systems can be afforded by means of algorithmic methodologies. A large range of approaches based on the simulation of the behavior of the system have been reported to answer this problem. Their main advantage consists of being applicable to most of the systems. An important drawback is the significant computational resources required to perform an exhaustive exploration of the state space due to the combinatorial explosion. A manual choice of a reduced set of configurations to be simulated can be improved by the use of parametric Petri nets and a metaheuristic search of the most promising ones. In this paper, a review of some definitions of parametric Petri net found in the literature is presented, as well as a definition for the general framework of stating optimization problems of both, the operation and the design of the model of the DES. Moreover, a methodology to obtain such a parametric Petri net, called compound Petri net, from an easier-to-obtain set of alternative Petri nets is proposed and an application example is given.

Fieldbus provides real-time data communication among field devices in process control and factory automation systems. IEC and ISA recently approved the Committee Draft of the data link layer of fieldbus standard for use in industrial control systems. The data link layer of IEC/ISA fieldbus is operated on the basis of token-passing and scheduling mechanisms. In this paper, the authors analyze the performance characteristics of the IEC/ISA fieldbus, especially the capability of real-time data transmission. A discrete-event simulation model of the data link layer is developed. Using the simulation model, this paper identifies the network parameters that influence the performance of priority mechanism and real-time data transmission, and analyzes the delay performance of IEC/ISA fieldbus with respect to the change of the network parameters. The fieldbus simulation model also integrates a continuous-time simulation model of a control system as an application process. Using the simulation model, this paper investigates the effect of network-induced delay on the performance of a control system.

The diagnosability condition for a Discrete Event System (DES) model requires that there exists no failureindeterminate cycles in the DES diagnoser for all failure types. This stringent requirement of DES diagnosability condition renders many systems non-diagnosable. I-diagnosability framework provides a weaker notion of diagnosability than DES diagnosability by considering only those failures that are followed by certain observable event(s) known as indicator events. However, some systems are I-non-diagnosable even in the presence of an indicator event following the failure event. In this paper, we propose I2-diagnosability framework overcomes the shortcomings of the I-diagnosability framework. In I2-DES framework an empowering event ensures that the indicator event sensitizes the failure successfully. We have considered a practical example of Advanced Stealth Man in the Middle attack in Wi-Fi networks to demonstrate the effectiveness of the proposed I2-DES framework wherein the I-DES framework fails.

The paper addresses finite state machines which provide suitable mathematical models for discrete-event dynamical systems. Boolean automata are of particular interest. Different from classical automata theory, an arithmetic representation of Boolean functions is used based on multilinear polynomials. By this technique finite automata are imbedded in the Euclidean vector space which allows to detect a closer relationship between discrete-event systems and classical discrete-time systems. The problem of self-regulation of binary dynamical systems is interpreted in terms of feedback control structures. As a special class, systems which are linear in the controls are considered. It is shown that multilinear state feedback can be utilized to globally linearize the over-all system. The design equations turn out to be linear with respect to the controller parameters in this case. An illustrative example is included.

This paper presents an approach to perform Activity Based Costing (ABC) with Petri nets. ABC is a powerful methodology to calculate various of discrete event systems (e.g. production systems). Petri net models of discrete event systems are easy to create, comprehend, and to perform analysis, the mathematics behind Petri nets is also easy to grasp. This paper shows how ABC can be performed with Petri nets, so that various involved in a discrete event system can be easily measured with the help of the Petri net model. After a short introduction to ABC and Petri nets, this paper shows the approach which basically embeds various cost drivers as firing costs and firing times of transitions in a Petri net model. This work also presents a case study that is done with GPenSIM, a toolbox realized with this approach.

The use of shared resources is a major problem occurring in discrete event (DE) systems, including manufacturing systems, computer systems, communication systems, highway/vehicle systems, and others. The issues involve problems of assignment of resources when the same resources are simultaneously requested by more than one job. Failure to suitably assign, or dispatch, resources in such situations can have serious deleterious effects on system performance, resulting in extreme cases in system deadlock [7]. Computer operating systems engineers and industrial engineers have used the concepts of circular wait (CW) and circular blocking in analysis of such phenomena [41, 24]. Various concepts in Petri nets (PN) are extremely useful for dealing with deadlock and a great deal of research has been done from the PN point of view (see references, especially [11, 14, 19]). The PN approaches are often based on the notion of the siphon, which indeed is called a “deadlock” in some works [26]. Unfortunately, it is known that many problems in scheduling, dispatching, and deadlock analysis are NP-hard [12], so that significant increases in computing power do not significantly improve computational ability. Neither PN nor CW approaches have addressed this issue.

From Goal Modeling of Real-time Control System to RT-DEVS Safety Properties Analysis

Modelling Basic Discrete Event Systems - A Key Factor in Supporting the Representation and Analysis of Complex Production Systems