• L. A. Kleiman Perm National Research Polytechnic University, Perm, Russia.
  • V. I. Freyman Perm National Research Polytechnic University, Perm, Russia.



autonomy, reliability, elements of an information management system, diagnostics, performance characteristics, dynamic distribution algorithm, software model, built-in test diagnostics.


Context. In the modern world, information management systems have become widespread. This make it possible to automate the technological processes of enterprises of various sizes. Many information management systems include wireless and autonomous elements. Autonomy, in this case, means the ability of the system elements to function for a certain time without additional energy supply. In this regard, such a parameter of operational reliability as the battery life of a system element becomes one of the most important. One of the main tools for improving the reliability and fault tolerance of information management system elements – is the use of a modern diagnostic system.

Objective. The aim of the work is to develop a method for increasing the reliability of the functioning of autonomous elements of information management systems. It includes the creation of a model of an information management system and an algorithm for reasonable redistribution of diagnostic functions, as well as a software implementation of the developed algorithm, which confirms its higher reliability indicators in comparison with other algorithms.

Methods. The basic model was the Preparata-Metz-Chen model. On its basis, a new model of the system was built, including the structural and logical description of the elements and the determination of the way of their interaction. The elements were classified by the degree of criticality of the functions performed in the system. On the basis of the developed model and description of the elements, an algorithm was developed for the reasonable redistribution of the diagnostic load, which made it possible to reduce the average energy consumption of the elements and thereby improve the reliability indicators. A software implementation of the developed algorithm was created, which allows to numerically evaluate its advantages. The developed and existing algorithms were compared.

Results. A model of information management system has been developed. In such a system, it is proposed to use an integrated test diagnostics system. This diagnostic system implements algorithms for redistributing the diagnostic load. To determine the importance of the characteristics taken into account, a linear criterion was chosen, as the most studied and fastest in application. A software model, that implements the developed algorithm and makes it possible to compare it with existing algorithms, has been developed. A study of the software model with various parameters was carried out and, based on the results of the software simulation, conclusions were drawn about the possibilities of improving the algorithm and directions for further scientific research were formulated.

Conclusions. The usage of the developed algorithm makes it possible to increase such a characteristic of the reliability of the elements of the information and control system as the mean time of failure-free operation (mean time between failures) by increasing the operating time of autonomous elements without recharging. When carrying out software modeling of the developed and existing algorithms, the advantages of the first were confirmed, and theoretical possibilities for its improvement were formulated.

Author Biographies

L. A. Kleiman , Perm National Research Polytechnic University, Perm, Russia.

Postgraduate student, Department «Automatics and telemechanics».

V. I. Freyman , Perm National Research Polytechnic University, Perm, Russia.

Dr. Sc., Professor of the Department «Automatics and telemechanics».


Chadeev V. M., Aristova N. I. Automation of Autonomous Largescale Production Systems, Management of large – scale system development (MLSD) : 12th International Conference, Moscow, 01–03 October 2019 : proceedings. Los Alamitos, IEEE, 2019, pp. 1–4. DOI: 10.1109/MLSD.2019.8911013.

Karimireddy T., Zhang S. Optimization of Real-Time Transmission Reliability on Wireless Industrial Automation Networks, Automation and Computing (ICAC) : 24th International Conference, Newcastle upon Tyne, 06–07 September 2018 : proceedings. Los Alamitos, IEEE, 2018, pp. 1–6. DOI: 10.23919/IConAC.2018.8749112.

Manusov V. Z., Orlov D. V., Frolova V. V. Diagnostics of Technical State of Modern Transformer Equipment Using the Analytic Hierarchy Process, Environment and Electrical Engineering and Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) : IEEE International Conference, Palermo, 12–15 June 2018 : proceedings. Los Alamitos, IEEE, 2018, pp. 1–6. DOI: 10.1109/EEEIC.2018.8493904.

Zhang J., Huang K. Fault diagnosis of coal-mine-gas charging sensor networks using iterative learning-control algorithm, Physical Communication, 2020, Vol. 43, pp. 1–9. DOI: 10.1016/j.phycom.2020.101175.

Hiramoto Y., Ohtake S., Takahashi H. A Built-In SelfDiagnostic Mechanism for Delay Faults Based on SelfGeneration of Expected Signatures, Asian Test Symposium (ATS) : 28th IEEE, Kolkata, 10–13 December 2019: proceedings. Los Alamitos, IEEE, 2019, pp. 31–36. DOI: 10.1109/ATS47505.2019.000-4.

Fatullah M. A., Rahardjo A., Husnayain F. Analysis of Discharge Rate and Ambient Temperature Effects on Lead Acid Battery Capacity, Innovative Research and Development (ICIRD) : 2nd IEEE International Conference, Jakarta, 28–29 June 2019 : proceedings. Los Alamitos, IEEE, 2019, pp. 1–5. DOI: 10.1109/ICIRD47319.2019.9074667.

Houankpo H. G., Kozyrev D. V., Nibasumba E. et al Mathematical Model for Reliability Analysis of a Heterogeneous Redundant Data Transmission System, Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) : The 12th International Congress, Brno, 01–03 October 2020 : proceedings. Los Alamitos, IEEE, 2020, pp. 189–194. DOI: 10.1109/ICUMT51630.2020.9222431.

Vedeshenkov V. A., Kurako E. A., Lebedev V. N. Diagnosability of digital systems structured as minimal quasicomplete 7 × 7 graph, Automation and Remote Control, 2016, Vol. 77, No. 3, pp. 485–494. DOI: 10.1134/S0005117916030103.

Aminev D. A., Zhurkov A. P., Kozyrev D. V. Multi-state Diagnostics for Distributed Radio Direction Finding System, Distributed Computer and Communication Networks (DCCN) : 20th International Conference, Moscow, 25–29 September 2017 : proceedings. Cham, Springer, 2017, pp. 443–452. DOI: 10.1007/978-3-319-66836-9_37.

Kim W., Braun J. E. Development, implementation, and evaluation of a fault detection and diagnostics system based on integrated virtual sensors and fault impact models, Energy and Buildings, 2020, Vol. 228, pp. 1–13. DOI: 10.1016/j.enbuild.2020.110368.

Li X., Hu Y., Li M. et al. Fault diagnostics between different type of components: A transfer learning approach, Applied Soft Computing, 2020, Vol. 86, pp. 1–11. DOI: 10.1016/j.asoc.2019.105950.

Dowdeswell B. Sinha R., MacDonell S. G. Finding faults: A scoping study of fault diagnostics for Industrial Cyber-Physical Systems, Journal of Systems and Software, 2020, Vol. 168, pp. 1–16. DOI: 10.1016/j.jss.2020.110638.

Freyman, V. I., Bezukladnikov I. I. The application of soft decision making on decoding and assessment of test diagnosing results within control systems elements, Soft Computing and Measurements (SCM) : XX IEEE International Conference, Saint-Petersburg, 24–26 May 2017 : proceedings. Los Alamitos, IEEE, 2017, pp. 124–128. DOI: 10.1109/SCM.2017.7970515.

Freyman V. I. Methods and algorithms of soft decoding for signals within information transmission channels between control systems elements, Radio Electronics, Computer Science, Control, 2018, No. 4, pp. 226–235. DOI: 10.15588/1607-32742018-4-22.

Wang S., Wang Z. The g-Good-Neighbor Diagnosability of Bubble-Sort Graphs under Preparata, Metze, and Chien’s (PMC) Model and Maeng and Malek’s (MM)* Model, Information, 2019, No. 10, pp. 1–14. DOI: 10.3390/info10010021.

Chien C., Wang Y., Lian F. Design and Analysis of Adaptive Iterative Learning Control for Iteration-varying Nonlinear Systems, Data Driven Control and Learning Systems (DDCLS) : 7th IEEE Conference, Enshi, 25–27 May 2018 : proceedings. Los Alamitos, IEEE, 2018, pp. 469–474. DOI: 10.1109/DDCLS.2018.8516070.

Gordievsky E., Sirotkin E., Miroshnichenko A. Development of Mobile Power Complex Model on Renewable Energy Sources for Autonomous Electrical Supply of Russian Far Eastern Region, Electrical Power Engineering (UralCon) : International Ural Conference, Chelyabinsk, 01–03 October 2019 : proceedings. Los Alamitos, IEEE, 2019, pp. 148–153. DOI: 10.1109/URALCON.2019.8877665.

Moore C. L., Khalsa P. S., Yilk T. A. et al. Monitoring High Performance Computing Systems for the End User, Cluster Computing : 2015 IEEE International Conference, Chicago, 08–11 September 2015 : proceedings. Los Alamitos, IEEE, 2015, pp. 714–716. DOI: 10.1109/CLUSTER.2015.124.

Podinovskii V. V. Decision under Multiple Estimates for the Importance Coefficients of Criteria and Probabilities of Values of Uncertain Factors in the Aim Function, Automation and Remote Control, 2004, Vol. 65, pp. 1817–1833. DOI: 10.1023/B:AURC.0000047896.61645.43.

Sun G., Hu Q., Zhang Q. et al. Fault diagnosis for rotating machinery based on artificial immune algorithm and evidence theory, Control and Decision (CCDC) : 27th International Conference, Qingdao, 23–25 May 2015 : proceedings. Los Alamitos, IEEE, 2015, pp. 2975–2979. DOI: 10.1109/CCDC.2015.7162380.

Dasari H. C., Joyce J., Jyoti Y. et al. Analysis on Web Frameworks, Journal of Physics : Conference Series, 2019, Vol. 1362, pp. 1–6. DOI: 10.1088/1742-6596/1362/1/012114.

Djuraev R. X., Djabbarov S. Y., Toshtemirov T. Q. Analysis Of The Relationship Between The Indicators Of Controllability And Reliability Characteristics Of Data Transmission Systems, Information Science and Communications Technologies (ICISCT) : International Conference, Tashkent, 04–06 November 2019 : proceedings. Los Alamitos, IEEE, 2019, pp. 1–4. DOI: 10.1109/ICISCT47635.2019.9011980.




How to Cite

Kleiman , L. A. ., & Freyman , V. I. (2021). IMPROVING THE FUNCTIONING RELIABILITY OF THE INFORMATION MANAGEMENT SYSTEM ELEMENTS, USING BUILT-IN DIAGNOSTIC TOOLS . Radio Electronics, Computer Science, Control, 1(1), 158–171.



Progressive information technologies