Year: 2026
Type: article
Abstract: This article originally integrates an approach to turbo-compressor analysis, combining performance evaluation with modern diagnostic tools, and offers a fresh perspective that distinguishes your work from more conventional studies. Significantly, the research topic of turbo-compressor maintenance is of paramount importance to industrial efficiency and reliability and its exploration of this area contributes valuable knowledge to the field. Overall, the current organization is very easy to understand and logically structured. The paper proposes a comprehensive framework for intelligent maintenance and performance optimization of industrial turbo-compressors. The core contributions include, firstly, establishing a graphical framework linking mechanical analysis of key compressor components (impeller/rotor/seals/bearings) with real-time condition monitoring; secondly, integrating vibration analysis, oil analysis, temperature/pressure monitoring, and machine learning algorithms for fault prediction; and finally, specifying test procedures such as hydrostatic testing, over-speed testing, and mechanical run testing.
Source: Advanced Manufacturing Research
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7130837737