Development of a Committee of Artificial Neural Networks for the Performance Testing of Compressors for Thermal Machines in Very Reduced Times

This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized traditional methods. The method was developed aiming at its application on compressor manufacture lines and on 100% of the units produced. Artificial neural networks (ANNs) were used to establish a model able to infer the refrigeration capacity based on the data collected directly on the production line. The proposed method does not make use of refrigeration systems and also does not require using the compressor oil.

Aerodynamic Development of Stages for Industrial Centrifugal Compressors: Part 2 — Test Data Analysis, Correlation and Use

The considerable amount of experimental data collected on specifically designed single-stage test rigs are correlated so as to allow a straightforward use for the design and performance prediction of stage configurations needed for industrial compressor manufacture. Internal stage flow-field measurements are further analyzed by means of proper methods to achieve information valid for improving existing stage, fluid-dynamic models. Suitable use of the stage performance data allows the laying out of standard stage series of given geometries capable of satisfying a wide range of requirements without continuously resorting to specific, restricted application designs.