Quantitative analysis of information acquisition ability in cognitive testability

Cognitive testability is proposed for the future intelligent system. It plays an important role in improving the readiness, decreasing the life-cycle cost and meeting the requirements of the mission reliability. Information acquisition ability is the one of core elements of the system cognitive testability. It is the foundation of fault diagnosis, prognostics and support decision-making. Aiming at the problem how to check whether the acquired information meets the standard to implement its function, an information quantitative analysis method based on the system structure, performance and function is proposed. Firstly, the flow chart of establishing direct relation between information and design characteristics is established. A rule to connect the basic elements is given. It can help to establish linkages between information and design characteristics for the next part. Then, linkages between information and design characteristics are established. Mathematical definitions of this method are given. The system design characteristic coverage model is defined. The system structure, function and information correlation model is proposed. Finally, the information coverage rates are defined. The information-performance coverage rate, the information-function coverage rate, and the information-unit coverage rate are defined separately. The flow chart of quantitative analysis of the cognitive testability acquisition ability is established. It includes establishing basic elements, generating direct relationship between the elements, calculating of information coverage rates and analyzing the uncovered design characteristics of elements.