izpis_h1_title_alt

Identification of different manifestations of nonlinear stick-slip phenomena during creep groan braking noise by using the unsupervised learning algorithms k-means and self-organizing map
ID Prezelj, Jurij (Avtor), ID Murovec, Jure (Avtor), ID Huemer-Kals, Severin (Avtor), ID Häsler, Karl (Avtor), ID Fischer, Peter (Avtor)

.pdfPDF - Predstavitvena datoteka, prenos (5,82 MB)
MD5: BA943CA9E9A476F00C1EEBCB692DFD8F
URLURL - Izvorni URL, za dostop obiščite https://www.sciencedirect.com/science/article/pii/S0888327021007056 Povezava se odpre v novem oknu

Izvleček
Creep groan is a friction-induced, low-frequency vibration and noise phenomenon of a vehicleʼs brake system which is excited by a repeating stick-slip effect. Together with high influences of design and operational parameters, the non-linear stick-slip leads to an interesting bifurcation behaviour of creep groan. For objective rating procedures, detection and classification methods considering this bifurcation behaviour are necessary. Within this study, an approach based on acoustic emission is presented. The approach harnesses high-frequency acceleration contents that accompany creep groanʼs characteristic stick-slip transitions. Whereas low-frequency vibration contents below 500 Hz are mainly defined by the characteristics of the brake system and the suspension of the vehicle, vibrations in the high-frequency range above 10 kHz exhibit patterns of waveforms similar to the patterns of acoustic emission bursts. By applying non-overlapping high- and low-pass filters, a novel signal, enveloping these bursts, was created. This envelope bursts signal enables a precise detection and quantification of stick-slip transitions directly in time domain, and led to the development of a whole new set of vibration signal features. These nine signal features were used to feed the unsupervised classification algorithms k-means and Kohonenʼs self-organizing map, which delivered robust and meaningful results. Four different creep groan classes were detected, where each has shown to be linked to a specific creep groan manifestation: Low-frequency groan, high-frequency groan and two transition phenomena with two/three stick-slip events per cycle were found. Classification results and their linked mechanical behaviour suggest an interaction between two significant vibration patterns during creep groan, probably a longitudinal and a torsional displacement of the axle. Aside of deeper insights in creep groanʼs bifurcation behaviour, the presented study enables not only the identification of creep groan, but also the automatic classification of its manifestations in real-time, and therefore provides further possibilities for creep groan control methods.

Jezik:Angleški jezik
Ključne besede:brake NVH, signal processing, acoustic emission, signal features, unsupervised classification, real-time AE envelope
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2022
Št. strani:Str. 1-17
Številčenje:Vol. 166, art. 108349
PID:20.500.12556/RUL-130987 Povezava se odpre v novem oknu
UDK:534.83:681.8
ISSN pri članku:0888-3270
DOI:10.1016/j.ymssp.2021.108349 Povezava se odpre v novem oknu
COBISS.SI-ID:77015299 Povezava se odpre v novem oknu
Datum objave v RUL:21.09.2021
Število ogledov:683
Število prenosov:166
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
:
Kopiraj citat
Objavi na:Bookmark and Share

Gradivo je del revije

Naslov:Mechanical systems and signal processing
Skrajšan naslov:Mech. syst. signal process.
Založnik:Elsevier
ISSN:0888-3270
COBISS.SI-ID:169243 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:14.08.2021

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:hrup, zavore, digitalna obdelava signalov, akustična emisija, psihoakustične značilke, nenadzorovano učenje, vibracije

Projekti

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P2-0401
Naslov:Energetsko strojništvo

Podobna dela

Podobna dela v RUL:
Podobna dela v drugih slovenskih zbirkah:

Nazaj