In this paper, problems of the online diagnostics of multiple faults in large scale systems are presented. Possibilities of recognition of multiple faults based on the knowledge of signatures of the single faults are discussed. The distinction between simultaneous faults and the series of faults is introduced and defined. The necessary condition for diagnostic reasoning assuming an occurrence of multiple faults is formulated. This paper will show that multiple faults appearing simultaneously or within short time intervals are correctly isolated under the assumption of single faults, if the subsets of faults suitable for isolation are disjunctive. A novel, practical and easy to implement algorithm designed for reasoning multiple faults is presented. An industrial example of the online diagnostics of a steam-water line of the power boiler is given.

The definitions and conditions for fault isolability of single faults for various forms of the diagnostic relation are reviewed. Fault isolability and unisolability on the basis of a binary diagnostic matrix are analyzed. Definitions for conditional and unconditional isolability and unisolability on the basis of a fault information system (FIS), symptom sequences and directional residuals are formulated. General definitions for conditional and unconditional isolability and unisolability in the cases of simultaneous evaluation of diagnostic signal values and a sequence of symptoms are provided. A comprehensive example is discussed.

In this paper, graph of a process (GP) is introduced as a new formalization of causal graph useful in fault diagnosis. Faults are directly incorporated into the model. In this paper, we propose the concept of model structure (MS), which can be used for building fuzzy and neural models for fault detection. Algorithms for finding all MSs and methods for determining faults-symptoms relation are developed. This method is applicable to the design of model-based diagnostic systems, when only basic knowledge of the process to be diagnosed is available. No mathematical model is needed. This paper shows that GP can be constructed on the basis of process diagrams and expert knowledge. Models for fault detection can be built automatically from process measurements. Ideas are explained on a three-tank system example. In the last section, our proposed method is compared in detail with other existing approaches using qualitative models.