DEVELOPMENT ISSUES IN ALGORITHMS FOR SYSTEM LEVEL SELF-DIAGNOSIS
The paper deals with the problem of developing probabilistic algorithm for system level self-diagnosis. The main goal of the suggested algorithm is to minimize the mean time of its executing. The algorithm is based on the computing of the posterior probability of fault-free state of each system unit. Final decision about unit’s state is made on the chosen decision rule. The execution of the probabilistic algorithm is elucidated with the help of simple example and then explained for the case of more complex systems.
complex systems; self-diagnosis; probabilistic algorithm; decision rule
Barsi T., Grandoni T., Maestrini P.: A theory of diagnosability of digital systems. IEEE Trans. on Comput., Vol. C-25, No. 6, 1976, 585–593.
Blount M. L.: Probabilistic treatment of diagnosis in digital systems. 7th IEEE Int. Symp. On Fault-Tolerant Computing, 1977, 72–77.
Fujiwara H., Kinoshita K.: Some existence theorems for probabilistically diagnosable systems. IEEE Trans. on Comp. Vol. C-27, No. 4, 1981, 297–303.
Mallela S., Masson G.: Diagnosable systems for intermittent faults. IEEE Trans. Comput., Vol. C-27, No. 6, 1978, 560–566.
Mashkov V. A., Mashkov O.A.: Diagnosis of sensor networks applied for environment monitoring. Int. Journal “Ecological Sciences“. Vol. 7, No. 1, 2015, 120–130.
Preparata T., Metze G., Chien R.: On the connection assignment problem of diagnosable system. IEEE Transactions on Electronic Computers. Vol. EC-16, No. 12, 1967, 848–854.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.