METHODS OF TECHNOLOGICAL MACHINERY MONITORING AND FAULT DIAGNOSIS

Authors

  • Kayumov Ahror Muminjonovich Teacher, Fergana branch of the Tashkent university of information technologies named after Muhammad al-Khorazmi.

Keywords:

Technological machinery, Monitoring methods, Fault diagnosis, Sensor-based monitoring, Data analytics, Machine learning, Digital twin technology, Internet of Things (IoT), Expert systems.

Abstract

The continuous advancement of technological machinery in various industries necessitates effective monitoring and fault diagnosis methodologies to ensure optimal performance and minimize downtime. This paper explores diverse methods employed in the field of technological machinery monitoring and fault diagnosis, aiming to enhance reliability and efficiency.

Downloads

Published

2023-10-04

How to Cite

Kayumov Ahror Muminjonovich. (2023). METHODS OF TECHNOLOGICAL MACHINERY MONITORING AND FAULT DIAGNOSIS. Intent Research Scientific Journal, 2(10), 11–17. Retrieved from http://intentresearch.org/index.php/irsj/article/view/219

Issue

Vol. 2 No. 10 (2023): IRSJ

Section

Articles

License

You are free to:

  1. Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
  2. Adapt — remix, transform, and build upon the material for any purpose, even commercially.
  3. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.