Abstract
Aiming at solving the multiple fault diagnosis problem as well as the sequence of all the potential multiple faults simultaneously, a new multiple fault diagnosis method based on the dependency model method as well as the knowledge in test results and the prior probability of each fault type is proposed. Firstly, the dependency model of the system can be built and used to formulate the fault-test dependency matrix. Then, the dependency matrix is simplified according to the knowledge in the test results of the system. After that, the logic ‘OR’ operation is performed on the feature vectors of the fault status in the simplified dependency matrix to formulate the multiple fault dependency matrix. Finally, fault diagnosis is based on the multiple fault dependency matrix and the ranking of each fault type calculated basing on the prior probability of each fault status. An illustrative numerical example and a case study are presented to verify the effectiveness and superiority of the proposed method.
Highlights
Fault diagnosis is the basis of the maintenance work for complex equipment and systems, such as the components in an aircraft [1,2], a motor [3,4,5], a diesel engine [6], and so on [7]
After analyzing and building the signal flow graphs model of a complex system, the dependency model can be generated for the following fault diagnosis and maintenance work
To solve the dependency model-based multiple fault diagnosis problem is to locate a suspicious set of fault X ⊂ F based on the fault-test dependency matrix FT, the prior probability set of the fault states P and the set of the observation results R in a system
Summary
Fault diagnosis is the basis of the maintenance work for complex equipment and systems, such as the components in an aircraft [1,2], a motor [3,4,5], a diesel engine [6], and so on [7]. The whole diagnosis process only needs one cycle of testing and diagnosis procedure Since it requires all the symptoms or at least most of the symptoms in advance to gain the correct diagnosis results, the concurrent fault diagnosis method is more suitable for a system where abundant sensing information can be acquired. A typical method for concurrent diagnosis is that the fault prior probability of the components in the system is known, the posterior probability of each component can be calculated and the maximum posteriori probability will be used to determine the corresponding fault component. To address the multiple fault diagnosis problem as well as the sequence of all the potential multiple faults simultaneously, a new simple dependency model-based fault diagnosis method is proposed in this paper.
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