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检索条件"主题词=Programmable logic controllers"

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FAULT DIAGNOSIS OF TIMED EVENT SYSTEMS: AN EXPLORATION OF MACHINE LEARNING METHODS 15

FAULT DIAGNOSIS OF TIMED EVENT SYSTEMS: AN EXPLORATION OF MA...

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15th ASME International Manufacturing Science and Engineering Conference (MSEC)

作者： Cohen, Joseph Jiang, Baoyang Ni, Jun Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9780791884751

Especially common in discrete manufacturing, timed event systems often require a high degree of synchronization for healthy operation. Discrete event system methods have been used as mathematical tools to detect known faults, but do not scale well for problems with extensive variability in the normal class. A hybridized discrete event and data-driven method is suggested to supplement fault diagnosis in the case where failure patterns are not known in advance. A unique fault diagnosis framework consisting of signal data from programmable logic controllers, a Timed Petri Net of the normal process behavior, and machine learning algorithms is presented to improve fault diagnosis of timed event systems. Various supervised and unsupervised machine learning algorithms are explored as the methodology is implemented to a case study in semiconductor manufacturing. Stale-of-the-art classifiers such as artificial neural networks, support vector machines, and random forests are implemented and compared for handling multi-fault diagnosis using programmable logic controller signal data. For unsupervised learning, classifiers based on principal component analysis utilizing major and minor principal components are compared for anomaly detection. The rule-based extreme random forest classifier achieves the highest validation accuracy of 98% for multi-fault classification. Likewise, the unsupervised learning approach shows similar success, yielding anomaly detection rates of 98% with false alarms under 3%. The industrial feasibility of this method is notable, with the results achieved with a training set 99% smaller than the supervised learning classifiers.

关键词： Prognostics and health management Timed Petri Nets programmable logic controllers industrial big data principal component analysis

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HoneyPLC: A Next-Generation Honeypot for Industrial Control Systems 20

HoneyPLC: A Next-Generation Honeypot for Industrial Control ...

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ACM SIGSAC Conference on Computer and Communications Security (ACM CCS)

作者： Morales, Efren Lopez Rubio-Medrano, Carlos Doupe, Adam Shoshitaishvili, Yan Wang, Ruoyu Bao, Tiffany Ahn, Gail-Joon Arizona State Univ Tempe AZ 85287 USA Texas A&M Univ Corpus Christi TX USA Samsung Res Seoul South Korea

ISBN: (纸本)9781450370899

Industrial Control Systems (ICS) provide management and control capabilities for mission-critical utilities such as the nuclear, power, water, and transportation grids. Within ICS, programmable logic controllers (PLCs) play a key role as they serve as a convenient bridge between the cyber and the physical worlds, e.g., controlling centrifuge machines in nuclear power plants. The critical roles that ICS and PLCs play have made them the target of sophisticated cyberattacks that are designed to disrupt their operation, which creates both social unrest and financial losses. In this context, honeypots have been shown to be highly valuable tools for collecting real data, e.g., malware payload, to better understand the many different methods and strategies that attackers use. However, existing state-of-the-art honeypots for PLCs lack sophisticated service simulations that are required to obtain valuable data. Worse, they cannot adapt while ICS malware keeps evolving, and attack patterns become more sophisticated. To overcome these shortcomings, we present HoneyPLC, a high-interaction, extensible, and malware-collecting honeypot supporting a broad spectrum of PLCs models and vendors. Results from our experiments show that HoneyPLC exhibits a high level of camouflaging: it is identified as real devices by multiple widely used reconnaissance tools, including Nmap, Shodan's Honeyscore, the Siemens Step? Manager, PLCinject, and PLCScan, with a high level of confidence. We deployed HoneyPLC on Amazon AWS and recorded a large amount of interesting interactions over the Internet, showing not only that attackers are in fact targeting ICS systems, but also that HoneyPLC can effectively engage and deceive them while collecting data samples for future analysis.

关键词： industrial control systems programmable logic controllers honeypot

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A FIRMWARE VERIFICATION TOOL FOR programmable logic controllers

A FIRMWARE VERIFICATION TOOL FOR PROGRAMMABLE LOGIC CONTROLL...

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6th Annual IFIP Working Group 11.10 International Conference on Critical Infrastructure Protection (ICCIP)

作者： McMinn, Lucille Butts, Jonathan Air Force Inst Technol Comp Sci Wright Patterson AFB OH USA IFIP Working Grp 11 10 Crit Infrastruct Protect Washington DC USA

ISBN: (纸本)9783642357640

Current supervisory control and data acquisition (SCADA) systems do not have adequately tailored security solutions. programmable logic controllers (PLCs) in SCADA systems are particularly vulnerable due to a lack of firmware auditing capabilities. Since a PLC is a field device that directly connects to a physical system for monitoring and control, a compromise of its firmware could have devastating consequences. This paper describes a tool developed specifically for verifying PLC firmware in SCADA systems. The tool captures serial data during firmware uploads and verifies it against a known good firmware executable. It can also replay captured data and analyze firmware without the presence of a PLC. The tool does not require any modifications to a SCADA system and can be implemented on a variety of platforms. These features, along with the ability to isolate the tool from production systems and adapt it to various architectures, make the tool attractive for use in diverse SCADA environments.

关键词： programmable logic controllers firmware verification

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Towards predictive part quality and predictive maintenance in industrial machining - a data-driven approach 53

Towards predictive part quality and predictive maintenance i...

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53rd Annual Hawaii International Conference on System Sciences (HICSS)

作者： Rudolph, Laura Schoch, Jennifer Fromm, Hansjoerg Karlsruhe Inst Technol Karlsruhe Germany Daimler AG Stuttgart Germany

ISBN: (纸本)9780998133133

Programs such as Industry 4.0 and Internet of Things contain the promise of "intelligent production" with "smart services". In fact, great advances have already been made in sensor technology and machine connectivity. Production plants continuously generate and communicate large amounts of data and have become "cyber-physical systems". However, the task of gaining knowledge from these large amounts of data is still challenging. Data generated by numerical control (NC) and programmable logic controllers (NC) comes in a raw format that doesnt allow the application of analytical methods directly. Extensive preprocessing and feature engineering has to be applied to structure this data for further analysis. An important application is the timely detection of deviations in the production process which allows immediate reactions and adjustments of production parameters or indicates the necessity of a predictive maintenance action. In our research, we aimed at the identification of special deviant behavior of a grinding machine based on NC data. One finding wast the distinguishing the warm-up program from regular production and the other to recognize imprecise identification of the grinding process window. Both tasks could be solved with extensive preprocessing of the raw data, appropriate feature extraction and feature reduction, and the subsequent application of a clustering algorithm.

关键词： programmable logic controllers

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Educational Platform for Simulating the Operation of an Automatic Car Wash Machine

Educational Platform for Simulating the Operation of an Auto...

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International Symposium on Fundamentals of Electrical Engineering (ISFEE)

作者： Saracin, Cristina Gabriela Ionita, Andrei Univ Politehn Bucuresti Elect Engn Bucharest Romania

ISBN: (纸本)9781728190389

This paper presents the practical implementation of an educational platform that intends to present the physical scale model construction and operation of an automatic car wash machine. The study of this educational platform aims to familiarize the students with modern automation equipment such as smart relays and programmable logic controllers (PLCs). The first part of the paper, it is described the automation equipment used and the construction of the educational platform in terms of hardware and software. In the second part is described its effective operation and its possibilities. The paper closely follows both the physical implementation of the educational platform and the full understanding of the operation of intelligent relays or PLCs and their programming in an automated industrial process.

关键词： intelligent relays programmable logic controllers automatic car wash educational platform

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On the Measurement of Software Complexity for PLC Industrial Control Systems using TIQVA 20

On the Measurement of Software Complexity for PLC Industrial...

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35th Annual ACM Symposium on Applied Computing (SAC)

作者： Muslija, Adnan Enoiu, Eduard Malardalen Univ Vasteras Sweden

ISBN: (纸本)9781450368667

In the safety-critical domain (e.g. transportation, nuclear, aerospace and automotive), large-scale embedded systems implemented using programmable logic controllers (PLCs) are widely used to provide supervisory control. Software complexity metrics, such as code size and cyclomatic complexity, have been used in the software engineering community for predicting quality metrics such as maintainability, bug proneness and robustness. However, since there is no available approach and tool support for measuring software complexity of PLC programs, we developed a tool called TIQVA in an effort to measure complexity for this type of software. We show how to measure different software complexity metrics such as lines of code, cyclomatic complexity, and information flow for a popular PLC programming language named Function Block Diagram (FBD). We evaluate the tool using data provided by Bombardier Transportation from a Train Control Management System (TCMS). In addition, we report some empirical and industrial evidence showing how TIQVA can be used to provide some experimental evidence to support the use of these metrics to estimate testing effort for an industrial control software. The results from this evaluation indicate that other specific dimensions of PLC programs (e.g., function block relationships, block coupling and timing) could be used to improve the measurement of complexity for industrial embedded software.

关键词： programmable logic controllers

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Data Logging and Reconstruction of Discrete-event System Behavior 16

Data Logging and Reconstruction of Discrete-event System Beh...

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16th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Reijnen, F. F. H. Van de Mortel-Fronczak, J. M. Rooda, J. E. Eindhoven Univ Technol Dept Mech Engn Eindhoven Netherlands

ISBN: (纸本)9781728177090

In case of malfunctions or accidents related to an infrastructural system, it is useful to reconstruct and analyze the behavior that led to such an undesired situation. Understanding the behavior can help in improving the plant and the supervisory controller such that this situation is not encountered again. Many computer-controller mechanical systems use programmable logic controllers (PLCs) to implement the supervisory controller and to collect data from the system. Currently, incident analysis for PLCs often consists of plotting actuator and sensor signals to reconstruct and analyze the behavior. This way of analyzing is laborious and difficult to interpret for engineers not familiar with the system. In this paper, a different behavioral reconstruction and analysis method is proposed. In this method, models developed during the design of the supervisory controller are reused. From the collected data, a finite-state automaton is constructed. This automaton can be used for behavioral reconstruction via simulation, which is simpler and more intuitive. Moreover, by comparing the logged behavior with the behavior defined in the available models, faults can be identified. As a proof of concept, the behavior of a real movable bridge has been logged from a PLC, reconstructed, simulated, and analyzed.

关键词： programmable logic controllers

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Utilizing Timed Petri Nets to Guide Data-Driven Fault Diagnosis of PLC-Timed Event Systems 11

Utilizing Timed Petri Nets to Guide Data-Driven Fault Diagno...

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Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS)

作者： Cohen, Joseph Jiang, Baoyang Ni, Jun Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Foxconn Ind Internet Technol Serv Business Grp Shenzhen Peoples R China

ISBN: (纸本)9781728197326

Highly synchronized timed event systems managed by programmable logic controllers are ubiquitous in manufacturing. Discrete event system methods such as finite state machines and Petri Nets have been useful for diagnosing known faults in such systems. However, existing methods do not scale as well for practical applications where faulty behavior is not fully known and event timing may vary. With the advent of big data, a new methodology is presented that strengthens fault diagnosis capabilities utilizing machine learning and Timed Petri Nets. The hybrid approach consists of building a Timed Petri Net model of the normal process to help select discriminating features based on timed event sequences. This work focuses on modeling Timed Petri Nets to serve as knowledge representations of the nominal process behavior to guide data-driven fault diagnosis of timed event systems. A methodology based on identification of observable events is introduced, consisting of three different and complementary heuristics including demarcating periods, modeling concurrencies, and imposing synchronizations. Then, using features selected by using the Timed Petri Net, a nonlinear SVM is implemented for multiclass fault classification. The proposed framework is applied to an existing semiconductor manufacturing process with events timed via binary programmable logic controller signals. With over 97% validation accuracy achieved for fault diagnosis, the hybrid modeling approach shows promise for smart manufacturing applications.

关键词： artificial intelligence Timed Petri Nets fault diagnosis fault classification smart manufacturing programmable logic controllers support vector machines discrete event systems

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An approach for resource Function Block generation: Towards RAMI4.0-compliant PLC Programming 18

An approach for resource Function Block generation: Towards ...

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18th IEEE International Conference on Industrial Informatics (INDIN)

作者： Zhang, Jiayi Ahmad, Bilal Harrison, Robert Colombo, Armando Walter Raasch, Steffen Univ Warwick WMG Coventry W Midlands England Univ Emden Emden Germany

ISBN: (纸本)9781728149646

Digital modelling and simulation of manufacturing processes find increasing use in the manufacturing industry. This provides an opportunity to use model information and carry them over into the software development phase to realise automatic PLC code generation. This paper extends the work presented in [1] to enable generation of function blocks for resource components rather than manually coding FBs. The approach is based on mapping table based that allow users to select required functionality, such as auto and manual control, diagnostic, return to initial position for machine components. This mapping table is filled by a programmer and links the information together. The approach provides a structured code that is generated in the IEC 61131-3 Structured Text. Additionally, the paper presents a use case as a proof of concept implementation. The approach is formalized and justified from the viewpoint of the RAMI4.0 specification and resulted in between 62 - 81 per cent time saving compared to manual coding of the FBs.

关键词： programmable logic controllers code generation 3D simulation RAMI4.0 IEC 61131-3 function blocks

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Design of an Electronic Coupling to Control Speed of Motor on a Conveyor Belt Using IoT

Design of an Electronic Coupling to Control Speed of Motor o...

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IEEE International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Ulices, Camacho Irma, Martinez Carlos, Juarez Autonomous Univ Mexico State UAEM Tianguistenco Profess Acad Unit Toluca Estado De Mexic Mexico

ISBN: (纸本)9781728199047

An advanced production ecosystem, automated and interconnected by the development of new technologies in industrial systems is known as Industry 4.0. The contribution of different technologies supported by cyber-physical systems whose principle of operation is to monitor and control manufacturing processes through computer-based algorithms connected to the Internet. this allows to have a Machine-to-Machine (M2M) communication system supervised and controlled for decision making. This paper will focus on the update of the design and construction of an electronic coupling device for making Industrial Internet of Things (IIoT) connections in a conventional programmable logic controllers (PLC). In this work a SIMATIC S7-200 PLC is used, where a Nodemcu Esp8266 WIFI card is coupled through the inputs and outputs of the device to monitor and control the shifting process of a product distribution hand. A method is proposed to modify the speed of motor using an HC-SR04 sensor to determine the amount of material corresponding to the PLC.

关键词： Internet of Things programmable logic controllers Speed Control Wifi

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