Noise Source Localisation in a Low Speed Automotive Engine Cooling Module
Bibliographic record
Abstract
The sound generated by rotating machines is a topic that is more and more considered. In fact, this noise is an environmental concern in many industrial fields. The rotating machine studied here is an automotive engine cooling fan system. The noise produced by these fans is a major contributor to the total radiated noise and in certain cases it dominates other sources like the engine or the tires. Usually, the fan is extracting the air through a heat exchanger where a coolant fluid is circulating through a network of tubing. The heat exchanger is usually located close to the fan on its suction side. This creates a turbulent flow and participates to the generation of broadband noise. As the module is located in the engine bay, the upstream flow is distorted which leads to a strong tonal noise contribution. The impact of those distortion on the blades or struts generates tonal noise. The article aims to evaluate the contribution of acoustic sources located on the rotor blades. The source localization for rotating machine should take into account the Doppler effect as the sources are rotating with the fan. Classical beamforming works but it leads to continuous annulus sources. Sitjsma et al. 1 propose to solve this problem by using a transfer function for a moving monopole source in uniform flow to reconstruct the signal in the time domain and develop an algorithm able to deal with rotating sources, Autord ROtating Source Identifier (ROSI). Using this method, the measurement of the sound pressure of rotating sources can be done using an array of microphones. The proper implementation of the method was verified using the benchmark from 2. In the present study, a 60-microphones logarithmic array was used and the reconstruction of sound pressure level was done in third octave bands. Measurements were done in different rotational velocity of the fan in the anechoic chamber of Sherbrooke's university (UdeS) without any other flow restriction than the heat exchanger itself. A measurement was done at full RPM with and without heat exchanger to compare if it is transparent acoustically. The Directivity measurements were conducted as well. Both method has been compared to the central microphone of the microphone array. The present paper is a part of a collaborative project between UdeS and Von Karman Institute (VKI). The major aim is to conduct an experimental investigation of the fan noise in two different facilities and to compare the results. 1 P, Sijtsma and S, Oerlemans and H, Holthusen. "Location of rotating sources by phased array measurements'', AIAA 2001-2167, 2001 2 Herold, G. "Microphone Array Benchmark b11: rotating points sources'', 2017
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".