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The paper presents an effective and efficient method for sensor fault detection and identification within a large group of sensors based upon hierarchical cluster analysis. Fingerprints of the hierarchical clustering dendrograms are found for normal operation using normalized data, and sensor faults are detected through cluster changes occurring in the dendrogram. The proposed strategy is built into...
Developing a fault detection and diagnosis system of complex processes usually involve large volumes of highly correlated data. In the complex aluminium smelting process, there are difficulties in isolating historical data into different classes of faults for developing a fault diagnostic model. This paper presents a new application of using a data mining tool, k-means clustering in order to determine...
The paper presents an efficient approach for applied sensor fault detection based on an integration of principal component analysis (PCA) and artificial neural networks (ANNs). Specifically, PCA-based y-indices are introduced to measure the differences between groups of sensor readings in a time rolling window, and the relative merits of three types of ANNs are compared for operation classification...
A real-time process monitoring system for detecting faults within aluminium reduction cells is presented in this paper. This system is developed using an integration of MPCA and Euclidean distances. MPCA is used to detect the specific faults during process monitoring whereas dynamic Euclidean distances are used to diagnose the faults. Results from real-data analysis show that this approach is effective...
A parity space approach to fault detection by an optimal measurement selection is proposed for networked control systems (NCS). A distributed process, decomposed into p sub-processes with different sampling times, is modeled as a linear time-invariant discrete-time system by means of the lifting technique. In order to reduce the network load and data transmission cost, an optimal scheme, which manages...
The focus of this research was to design a framework to create highly autonomous fault-tolerant distributed sensor networks with plug-and-play capabilities. This would enable diagnosis of faulty sensors and reconfiguration of the network in real time to ensure that the control of the manufacturing process can continue with accurate information in presence of sensor and processing element faults. The...
Input-predicate/output (IP/O)n-chains coverage criterion, originally proposed for black-box testing of telecommunications software, is adapted to white-box testing of programs written in block-structured languages. This criterion is based on the analysis of the effects of inputs on predicates and outputs in a program. It requires that each such effect in a program is examined at least once during...
Based on the achievable variance of the control outputs, a fault diagnosis of cascade control systems is developed. Without any prior knowledge of the complex operating processes and/or a prior external input to perturb the operating system, the accurate fault identification can be achieved by a series of the statistical hypothesis procedure that is applied to the current measured data. To isolate...
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