An efficient real-time method of analysis for non-coherent fault trees

Fault tree analysis is commonly used to assess the reliability of potentially hazardous industrial systems. The type of logic is usually restricted to AND and OR gates which makes the fault tree structure coherent. In non-coherent structures not only components’ failures but also components’ working states contribute to the failure of the system. The qualitative and quantitative analyses of such fault trees can present additional difficulties when compared to the coherent versions. It is shown that the Binary Decision Diagram (BDD) method can overcome some of the difficulties in the analysis of non-coherent fault trees. This paper presents the conversion process of non-coherent fault trees to BDDs. A fault tree is converted to a BDD that represents the system structure function (SFBDD). A SFBDD can then be used to quantify the system failure parameters but is not suitable for the qualitative analysis. Established methods, such as the meta-products BDD method, the zero-suppressed BDD (ZBDD) method and the labelled BDD (L-BDD) method, require an additional BDD that contains all prime implicant sets. The process using some of the methods can be time consuming and not very efficient. In addition, in real time applications the conversion process is less important and the requirement is to provide an efficient analysis. Recent uses of the BDD method are for real time system prognosis. In such situations as events happen, or failures occur the prediction of mission success is updated and used in the decision making process. Both qualitative and quantitative assessment are required for the decision making. Under these conditions fast processing and small storage requirements are essential. Fast processing is a feature of the BDD method. It would be advantageous if a single BDD structure could be used for both the qualitative and quantitative analyses. Therefore, a new method, the ternary decision diagram (TDD) method, is presented in this paper, where a fault tree is converted to a TDD that allows both qualitative and quantitative analyses and no additional BDDs are required. The efficiency of the four methods is compared using an example fault tree library

An efficient real-time method of analysis for non-coherent fault trees

Fault tree analysis is commonly used to assess the reliability of potentially hazardous industrial systems. The type of logic is usually restricted to AND and OR gates which makes the fault tree structure coherent. In non-coherent structures not only components’ failures but also components’ working states contribute to the failure of the system. The qualitative and quantitative analyses of such fault trees can present additional difficulties when compared to the coherent versions. It is shown that the Binary Decision Diagram (BDD) method can overcome some of the difficulties in the analysis of non-coherent fault trees. This paper presents the conversion process of non-coherent fault trees to BDDs. A fault tree is converted to a BDD that represents the system structure function (SFBDD). A SFBDD can then be used to quantify the system failure parameters but is not suitable for the qualitative analysis. Established methods, such as the meta-products BDD method, the zero-suppressed BDD (ZBDD) method and the labelled BDD (L-BDD) method, require an additional BDD that contains all prime implicant sets. The process using some of the methods can be time consuming and not very efficient. In addition, in real time applications the conversion process is less important and the requirement is to provide an efficient analysis. Recent uses of the BDD method are for real time system prognosis. In such situations as events happen, or failures occur the prediction of mission success is updated and used in the decision making process. Both qualitative and quantitative assessment are required for the decision making. Under these conditions fast processing and small storage requirements are essential. Fast processing is a feature of the BDD method. It would be advantageous if a single BDD structure could be used for both the qualitative and quantitative analyses. Therefore, a new method, the ternary decision diagram (TDD) method, is presented in this paper, where a fault tree is converted to a TDD that allows both qualitative and quantitative analyses and no additional BDDs are required. The efficiency of the four methods is compared using an example fault tree library

Timed Fault Tree Models of the China Yongwen Railway Accident

Safety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed Fault Trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide a safe time window to repair them. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system based on timed fault tree models. We demonstrate the applicability of our framework via a case study of the China Yongwen line railway accident