NDLI: DeviceNet network health monitoring using physical layer parameters

Content Provider	Springer Nature Link
Author	Lei, Yong Djurdjavic, Dragan Barajas, Leandro Workman, Gary Biller, Stephan Ni, Jun
Copyright Year	2009
Abstract	Since the 1980s, the manufacturing environment has seen the introduction of numerous sensor/actuator bus and network protocols for automation systems, which led to increased manufacturing productivity, improved inter- changeability of devices from different vendors, facilitated flexibility and reconfigurability for various applications and improved reliability, while reducing installation and maintenance costs. However, such heightened manufacturing integration facilitated by industrial networks also leads to dramatic consequences of improper or degraded network operation. This paper presents a novel Network Health Management system that provides diagnostic and prognostic information for DeviceNet at the device and network level. It extracts features from analog waveform communication signals, as well as logic and timing features from digital packet logs. These features are used to evaluate the network system performance degradation by applying multidimensional clustering techniques. In addition, this work proposes a hybrid prognostics structure using combined physical and logic layer features to provide fault location information that cannot easily be realized with analog or digital data independently. Furthermore, an intermittent connection diagnostic algorithm which analyzes patterns of interrupted and error packets on the network was developed. This tool can be used as a packet source identification method which uses joint analog features and digital information inferred from analog waveforms. A test-bed was constructed and the experiments of network impedance mismatch, cable degradation, and intermittent connections were conducted in laboratory environment. Experimental results show that the proposed system can detect degradations of the network and identify the location of the intermittent connection successfully. Field tests performed in an industrial environment were also conducted and their results are discussed.
Starting Page	289
Ending Page	299
Page Count	11
File Format	PDF
ISSN	09565515
Journal	Journal of Intelligent Manufacturing
Volume Number	22
Issue Number	2
e-ISSN	15728145
Language	English
Publisher	Springer US
Publisher Date	2009-08-09
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Industrial networks Field buses DeviceNet Fault diagnosis Network automation systems Network instrumentation Control , Robotics, Mechatronics Production/Logistics Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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