nach oben

Advances in Manufacturing

Erschienen in:

09.03.2022

An integrated machine-process-controller model to predict milling surface topography considering vibration suppression

verfasst von: Miao-Xian Guo, Jin Liu, Li-Mei Pan, Chong-Jun Wu, Xiao-Hui Jiang, Wei-Cheng Guo

Erschienen in: Advances in Manufacturing | Ausgabe 3/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Surface topography is an important factor in evaluating the surface integrity and service performance of milling parts. The dynamic characteristics of the manufacturing system and machining process parameters significantly influence the machining precision and surface quality of the parts, and the vibration control method is applied in high-precision milling to improve the machine quality. In this study, a novel surface topography model based on the dynamic characteristics of the process system, properties of the cutting process, and active vibration control system is theoretically developed and experimentally verified. The dynamic characteristics of the process system consist of the vibration of the machine tool and piezoelectric ceramic clamping system. The dynamic path trajectory influenced by the processing parameters and workpiece-tool parameters belongs to the property of the cutting process, while different algorithms of active vibration control are considered as controller factors. The milling surface topography can be predicted by considering all these factors. A series of experiments were conducted to verify the effectiveness and accuracy of the prediction model, and the results showed a good correlation between the theoretical analysis and the actual milled surfaces.

Vorheriger Artikel Relationship between dynamic characteristics of air film of aerostatic spindle and mid-frequency of surface topography

Nächster Artikel Continuous generating grinding method for beveloid gears and analysis of grinding characteristics

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Zhu L, Liu C (2020) Recent progress of chatter prediction, detection and suppression in milling. Mech Syst Signal Process 143:106840. https://doi.org/10.1016/j.ymssp.2020.106840CrossRef

Liu H, Song W, Niu Y et al (2021) A generalized cauchy method for remaining useful life prediction of wind turbine gearboxes. Mech Syst Signal Process 153:107471. https://doi.org/10.1016/j.ress.2020.107241CrossRef

Li W, Wang A, Gao X et al (2021) Development of multi-band tuned rail damper for rail vibration control. Appl Acoust 184:108370. https://doi.org/10.1016/j.apacoust.2021.108370

Li S, Sui J, Ding F et al (2021) Optimization of milling aluminum alloy 6061-T6 using modified Johnson-Cook model. Simul Model Pract Theory 111:102330. https://doi.org/10.1016/j.simpat.2021.102330CrossRef

Guo W, Wu C, Ding Z et al (2021) Prediction of surface roughness based on a hybrid feature selection method and long short-term memory network in grinding. Int J Adv Manuf Technol 112:2853–2871CrossRef

Pham T, Nguyen D, Banh T et al (2020) Experimental study on the chip morphology, tool-chip contact length, workpiece vibration, and surface roughness during high-speed face milling of A6061 aluminum alloy. Proc Inst Mech Eng Part B J Eng Manuf 234:610–620CrossRef

Matsumura M, Nozaki K, Yanaka W et al (2020) Optimization of milling condition of composite resin blocks for CAD/CAM to improve surface roughness and flexural strength. Dent Mater J 39:1057–1063CrossRef

Wang T, Wu X, Zhang G et al (2020) Theoretical study on the effects of the axial and radial runout and tool corner radius on surface roughness in slot micromilling process. Int J Adv Manuf Technol 108:1931–1944CrossRef

Liu C, He Y, Wang Y et al (2019) An investigation of surface topography and workpiece temperature in whirling milling machining. Int J Mech Sci 164:105182. https://doi.org/10.1016/j.ijmecsci.2019.105182CrossRef

10.

Lu X, Zhang H, Jia Z et al (2018) Floor surface roughness model considering tool vibration in the process of micro-milling. Int J Adv Manuf Technol 94:4415–4425CrossRef

11.

Mattia T, Paolo A, Michele M (2020) Surface morphology prediction model for milling operations. Int J Adv Manuf Technol 106:3189–3201CrossRef

12.

Wang Z, Wang B, Yuan J (2019) Modeling of surface topography based on cutting vibration in ball-end milling of thin-walled parts. Int J Adv Manuf Technol 101:1837–1854CrossRef

13.

Jing X, Lv R, Song B et al (2021) A novel run-out model based on spatial tool position for micro-milling force prediction. J Manuf Process 68:739–749CrossRef

14.

Costes J, Moreau V (2011) Surface roughness prediction in milling based on tool displacements. J Manuf Process 13:133–140CrossRef

15.

Pereira R, Marcos G (2021) Robust passive control methodology and aeroelastic behavior of composite panels with multimodal shunted piezoceramics in parallel. Compos Struct 262:113348. https://doi.org/10.1016/j.compstruct.2020.113348CrossRef

16.

Hu J, Habib G (2020) Friction-induced vibration suppression via the tuned mass damper: optimal tuning strategy. Lubricants 8:1–16CrossRef

17.

Wang F, Lee C, Zheng R (2020) Benefits of the inerter in vibration suppression of a milling machine. J Franklin Inst 356:7689–7703CrossRef

18.

Bolat FC, Sivrioglu S (2018) Active vibration suppression of elastic blade structure: using a novel magnetorheological layer patch. J Intell Mater Syst Struct 29:3792–3803CrossRef

19.

Sivrioglu S, Bolat FC (2020) Switching linear quadratic Gaussian control of a flexible blade structure containing magnetorheological fluid. Trans Inst Meas Control 42:618–627CrossRef

20.

Sivrioglu S, Bolat FC, Erturk E (2019) Active vibration control of a blade element with uncertainty modeling in PZT actuator force. Journal Vib Control 25:2721–2732MathSciNetCrossRef

21.

Paul S, Morales-Menendez R (2018) Active control of chatter in milling process using intelligent PD/PID control. IEEE Access 6:72698–72713CrossRef

22.

Zhang X, Wang C, Liu J et al (2019) Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators. Mech Syst Signal Process 120:808–835CrossRef

23.

Hadi M, Darus I, Tokhi M (2020) Active vibration control of a horizontal flexible plate structure using intelligent proportional-integral-derivative controller tuned by fuzzy logic and artificial bee colony algorithm. J Low Freq Noise Vib Active Control. https://doi.org/10.1177/1461348419852454CrossRef

24.

Zhang J, Liu C (2019) Chatter stability prediction of ball-end milling considering multi-mode regenerations. Int J Adv Manuf Technol 100:131–142CrossRef

25.

Li C, Li X, Huang S et al (2020) Ultra-precision grinding of Gd₃Ga₅O₁₂ crystals with graphene oxide coolant: material deformation mechanism and performance evaluation. J Manuf Process 61:417–427CrossRef

26.

Zhu D, Feng X, Xu X et al (2020) Robotic grinding of complex components: a step towards efficient and intelligent machining-challenges, solutions, and applications. Robot Comput Integr Manuf 65:101908. https://doi.org/10.1016/j.rcim.2019.101908CrossRef

27.

Zhuang K, Fu C, Weng J et al (2021) Cutting edge microgeometries in metal cutting: a review. Int J Adv Manuf Technol 116:2045–2092CrossRef

28.

Cabrera C, Araujo A, Castello D (2017) On the wavelet analysis of cutting forces for chatter identification in milling. Adv Manuf 5:130–142CrossRef

29.

Vasques CMA, Rodrigues JD (2007) Active vibration control of a smart beam through piezoelectric actuation and laser vibrometer sensing: simulation, design and experimental implementation. Smart Mater Struct 16:305–316CrossRef

30.

Jiang H, Long X, Meng G (2008) Study of the correlation between surface generation and cutting vibrations in peripheral milling. J Mater Process Technol 208:229–238CrossRef

31.

Chen C, Albert J (2008) Design and tuning of a fuzzy logic controller for micro-hole electrical discharge machining. J Manuf Process 10:61–73CrossRef

32.

Xiong J, Zhu B, Chen H et al (2020) Peak elimination of cross structures in wire and arc additive manufacturing using closed-loop control. J Manuf Process 58:368–376CrossRef

33.

Qu W, Sun J, Qiu Y (2004) Active control of vibration using a fuzzy control method. J Sound Vib 275:917–930MathSciNetCrossRef

34.

Zhang B, Dong W, Li X et al (2020) Design of active-passive composite vibration isolation system of magnetic levitation and spring based on fuzzy PID control. In: 2020 Chinese Automation Congress (CAC), 6–8 Nov 2020, Shanghai. https://doi.org/10.1109/CAC51589.2020.9326769

35.

Chen G, Li Y, Liu X (2018) Pose-dependent tool tip dynamics prediction using transfer learning. Int J Mach Tools Manuf 137:30–41CrossRef

36.

Yu Y, Lin C, Hu Y (2021) Study on simulation and experiment of non-circular gear surface topography in ball end milling. Int J Adv Manuf Technol 114:1913–1923CrossRef

37.

Kang WT, Derani MN, Ratnam MM (2021) Effect of vibration on surface roughness in finish turning: simulation study. Int J Simul Model 19:595–606CrossRef

Titel: An integrated machine-process-controller model to predict milling surface topography considering vibration suppression
verfasst von: Miao-Xian Guo
Jin Liu
Li-Mei Pan
Chong-Jun Wu
Xiao-Hui Jiang
Wei-Cheng Guo
Publikationsdatum: 09.03.2022
Verlag: Shanghai University
Erschienen in: Advances in Manufacturing / Ausgabe 3/2022
Print ISSN: 2095-3127
Elektronische ISSN: 2195-3597
DOI: https://doi.org/10.1007/s40436-021-00386-7

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 3/2022

Precision measurement and compensation of kinematic errors for industrial robots using artifact and machine learning

Effects of process parameters on periodic impact force exerting on cutting tool in ultrasonic vibration-assisted oblique turning

Relationship between dynamic characteristics of air film of aerostatic spindle and mid-frequency of surface topography

On-machine measurement of tool nose radius and wear during precision/ultra-precision machining

Model reconstruction for worn blades based on hybrid surface registrations

Research on the underlying mechanism behind abrasive flow machining on micro-slit structures and simulation of viscoelastic media

Premium Partner

Marktübersichten