Authors: I.A. Lobur, V.A. Negadaev, A.N. Gargaev, R.V. Kotlyarov

Title of the article: Automated system for diagnostics of the state of electric drive units

Year: 2022, Issue: 3, Pages: 59-66

Branch of knowledge: 09.05.03 Electrotechnical complexes and systems

Index UDK: 681.5.08:62-83

DOI: 10.26730/1816-4528-2022-3-59-66

Abstract: The effective functioning of modern enterprises of the energy industry is based on the reliable operation of units with electric drives. An urgent task is to maintain the electric drive in working condition. The solution to the problem is not only regular maintenance of the electric motor, but also continuous monitoring of its condition during operation. An automated system for diagnosing the condition of electric drive units is proposed, which performs troubleshooting and prevention of failures and malfunctions of electric motors, maintaining operational indicators within the established limits, predicting the condition in order to maximize the life of the service units for their own needs. Possible sources of malfunction and methods of their diagnostics are identified. The technical means of ZETLAB have been selected, which allow timely diagnosis of emergency mode, timely detection of emerging problems and avoidance of equipment breakdown. The automated system for diagnosing the condition of electric drive units in order to increase the reliability of operation and data collection involves the input of several parameter signals in the backup mode. Block diagrams of algorithms for processing input signals by the data backup system have been developed. Python is used to implement the algorithms. The total costs of creating an automated diagnostic system without taking into account the costs of electricity consumption are determined. The authors believe that the introduction of an automated diagnostic system is economically feasible.

Key words: electric drive automated diagnostic system digital sensors ZETLAB Python

Receiving date: 10.12.2021

Approval date: 14.05.2022

Publication date: 01.07.2022

CITE DOWNLOAD