P
Ping Zhang
Researcher at Kaiserslautern University of Technology
Publications - 141
Citations - 4154
Ping Zhang is an academic researcher from Kaiserslautern University of Technology. The author has contributed to research in topics: Fault detection and isolation & Residual. The author has an hindex of 31, co-authored 129 publications receiving 3637 citations. Previous affiliations of Ping Zhang include Tsinghua University & European Union.
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A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process
TL;DR: A comparison study on the basic data-driven methods for process monitoring and fault diagnosis (PM–FD) based on the original ideas, implementation conditions, off-line design and on-line computation algorithms as well as computation complexity are discussed in detail.
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Subspace method aided data-driven design of fault detection and isolation systems
TL;DR: In this paper, the authors deal with data-driven design of fault detection and isolation (FDI) systems and identify a primary form of residual generators, instead of the process model, directly from test data and, based on it, design advanced FDI systems.
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A Generic Strategy for Fault-Tolerance in Control Systems Distributed Over a Network
Ron J. Patton,Chandrasekhar Kambhampati,Alessandro Casavola,Ping Zhang,Steven X. Ding,Dominique Sauter +5 more
TL;DR: In this paper, the authors provide a tutorial overview of fault-tolerant control over the network for network control systems (NCS) that are likely to lead to good fault tolerant control properties, subject to network faults.
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An Integrated Design Framework of Fault-Tolerant Wireless Networked Control Systems for Industrial Automatic Control Applications
TL;DR: The main objective is to achieve an integrated parameterization and design of the communication protocols, the control and fault diagnosis algorithms aiming at meeting high real-time requirements in industrial applications.
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On the application of PCA technique to fault diagnosis
TL;DR: This paper proposes a new test statistic, which is similar to the Hawkin's T 2h statistic but without the numerical drawback, and considers the off-set and scaling faults, and evaluates the test statistic by viewing its sensitivity to the faults.