Brake Squeal - Modeling and Experimental Investigation Using a Work Criterion
Bibliographic record
Abstract
Squealing automotive brakes are usually not accepted by customers. However, squealing is an omnipresent phenomenon in disc brakes at least in certain operation states. During the development process of new brakes, engineers succeed more or less in covering this phenomenon with tools like using shims, modifying the structure or varying the mounted pads. In 2002 Popp et al. [1] described the pre-conditions for positive work of the friction forces (i.e. excitation of squeal) based on a very simple model. The essential point in this model is a phase shift between the in-plane movement of the pad and the friction force. In [2] it was shown that it is possible to suppress actively brake squeal using this approach. Active pads with integrated piezoceramics were used as actuators. The authors of the present paper use multi body brake models for the investigation of the origin of the excitation mechanism by observing the work per period of the friction forces and comparing the results with the classic stability analysis. A measurement technique based on these theoretical investigations is developed for detecting parameter regions (e.g. for the brake pressure and corresponding squealing frequencies) which are suspicious for squeal. Considering two models of the brake, phase shifts between signals and measuring the work of the nonconservative forces are considered with respect to the question of detecting the tendency to squeal. Based on these theoretical results measurement procedures are developed and tested at test rigs at TU Berlin and TU Darmstadt. The results of this procedure coincide with results of state of the art experimental investigations but can be performed much faster. This new procedure yields even more significant results than the ones described in [2].
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".