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transferred to working feed velocities. To maintain or to get abetter workpiece quality at these velocities, higher cutting speedsare required as well.

Higher velocities and accelerations of each machine axis inducehigher dynamic loads, which affect the entire machine system, theenvironment and the peripherals. These loads generally enhancestructural vibration amplitudes which affect the production qualitynegatively and induce a high noise emission during machining.

The minimum requirements for the protection of workers fromrisks to their health and safety arising out of exposure to vibrationsand noisewere tightenedwith the ratication of theDirective 2003/10/EC by the European Parliament. More precisely, the limit andaction values in respect to the daily noise exposure levels and peaksound pressure levels were reduced by 5 dB(A) [1]. Besides the

machines with regard to these facts. Local encapsulation or passive

passive vibration reduction systems, the latter ones are able tocontrol the system behavior during machining by an adequatematerial and structure integration. Therefore, they are able tointerrupt the transmission path of the vibration energy.

Based on a systematic vibration and noise generation analysisthe design and test of an adaptronic system at wood machiningcenters were investigated.

2. Vibrations on woodworking machining centers

The structure of woodworking machining centers is predomi-nantly designed as an arm structure. This kind of structure is idealfor a complete machining of different workpiece geometries. Theworkpiece materials which are machined on these centers aremostly derived timber products for furniture industry and timber-

accessibility to the workpiece edges.Milling processes involve two kinds of motions. The primary

CIRP Annals - Manufacturing Technology 59 (2010) 395398

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Contents lists available at ScienceDirect

CIRP Annals - Manufa

s.edampingmethods generally used to counteract this problem do notmachining quality, the sound radiation of machines becomes animportant assessment benchmark for machine tools. A recentanalysis revealed that many workplaces in the woodworkingindustry exceed these new legal limits by far. Technologicaladvancements have to be made to improve the performance andsimultaneously reduce the vibration and noise emission of these

frame constructions, e.g. particle boards and MDF (mediumdensity berboard) panels. Stationary woodworking machiningcenters predominantly use a vacuum system as clamping device.By using this system, workpieces are neither damaged nordeformed during milling, drilling or sawing processes. The systemallows an arbitrary positioning of each suction block and a goodDevelopment of an active clamping sys

J. Hesselbach (2), H.-W. Hoffmeister, B.-C. Schulle

Institute of Machine Tools and Production Technology (IWF), Technische Universitat Br

1. Introduction

Current developments and research in the eld of stationarywoodworking machines mainly focus on an increase in produc-tivity. These developments are always associated with an increasein machine performance, which is connected with setting uphigher feed velocities. These machines actually reach rapid feedvelocities of up to y f 160m=min which cannot always be

A R T I C L E I N F O

Keywords:

Machine tool

Vibration

Adaptronic

A B S T R A C T

Noise emissions of up to 1

systems are predominant

These clamping systems en

this clamping method th

frequency domain during m

level is induced by these v

designed and implemente

the localization of the vib

system integration into th

research demonstrate the

journal homepage: http: / /eereduce thenoise level as desired. Besides, such solutionsparticularlyfor woodworking machining centers are limited to design aspects.An improved performance can only be realized by new machine

* Corresponding author.

0007-8506/$ see front matter 2010 CIRP.doi:10.1016/j.cirp.2010.03.079m for noise and vibration reduction

, K. Loeis

schweig, Langer Kamp 19b, 38106 Braunschweig, Germany

component design and new system developments. These may beachieved by the integration of active or adaptronic systems into themechanical components ofmachine tools. These systems,which arealso known as smart structures, usemulti-functional materials thatcan be used as sensors or actuators. By means of e.g. piezoelectricproperties, they can adapt independently to changing inuences ofthe surrounding or operation conditions [2,3]. In opposition to

B(A) occur during the machining of composite boards. Vacuum clamping

sed for machining particle boards on woodworking machining centers.

e a good accessibility to the workpiece edges during milling. As a result to

ards have non-clamped areas. Consequently they vibrate over a wide

hining. The quality of the particle board edges is reduced and a high noise

tions. An active clamping system based on piezo-stack actuators has been

reduce these vibration amplitudes. All required steps of its development,

ons and the noise emission, the mechanical and control design and the

achine table, are presented in this paper. The achieved results of this

icance of active systems in machine tools.

2010 CIRP.

cturing Technology

lsevier.com/cirp/default .aspmotion is realized by the revolution of the end milling tool and thesecondary is the infeedmotion. The necessary cutting force for chipremoval has to be absorbed by the tool cutting edge and theworkpiece. The cutting force is composed of an active and a passiveforce, which is perpendicular to theworking plane. The active forceFa can be divided into two components Ff and Fc which point into

d vi

J. Hesselbach et al. / CIRP Annals - Manufacturing Technology 59 (2010) 395398396the direction of the feed velocity y f and in the direction of thecutting speed yc (Fig. 1).

Therefore, the direction of the active force changes with theentrance angle of the cutting edge. Due to discontinuous cutting(with number of teeth z = 1), high dynamic loads also occur in thetooth contact zone. These loads which are induced by the cuttingforces lead to thermal loads and mechanical dynamic stresses andstrains. They spread out over the cutting tool and workpiece sideinto the machine structure (Fig. 1). Depending on the materialproperties of each component these loads consequently induceforced vibrations into the overall system composed of the machinestructure, the tool and the workpiece. The dynamic behavior of thesystem is described bymass, stiffness and damping characteristics.Each structure depending on the size of these values yieldsparticular mode shapes at specic natural frequencies indepen-dent of the dynamic loads which are acting on the structure.

The natural frequencies and the mode shapes of the machinestructure and the clamped workpiece were determined by anexperimental modal analysis. Analysis results show that theworkpiece has a 100 times higher dynamic compliance comparedto the tool and the machine structure, especially with thisclamping conguration. However, the main disadvantages of the

Fig. 1. Cutting force components anabove described clamping method are the free and overhangingareas of the boards. These non-clamped areas raise the dynamiccompliance of the workpieces. Consequently they are excitedduring high rate processing over a wide frequency range, whichincrease the risk of chipping along the workpiece edges.

The frequencies that occur during machining were analyzed.These have a signicant inuence on the dynamic behavior of theworkpiece and consequently on the vibrations and noise emission.During the milling process, the vibration amplitudes were

Fig. 2. Vibration amplitude (spectrogram) at the workpiece surface.measured with accelerometers on the workpiece surface. Therotation speed of the tool was na = 18,000 rpm. The spectrogram inFig. 2 of a measured signal shows the dominant vibrationfrequencies during idling (run-up and run-out) and machining.The maximum vibration amplitude is as expected at thefundamental frequency of 300 Hz. In this case a forced vibrationpropagates all over the workpiece due to its higher compliance.Besides the fundamental frequency of 300 Hz Fig. 2 shows that inthe frequency range of 05 kHz several harmonics are present.Therefore, the vibration is identied as forced impulse vibration.

Due to this kind of excitation, the workpiece will oscillateduring machining with a complex mode shape. The mode shape isa linear combination of all the modes at each natural frequencywhich lies in the vicinity of the fundamental excitation frequencyand their harmonics.

3. Noise emission on woodworking machining centers

The process forces which occur during machining induce directand indirect airborne sound in the tooth contact zone.

The direct airborne sound is composed of the idling sound of thetool and the impulse sound which results from the contact

bration propagation during milling.between tool and workpiece. The second type of sound isgenerated from the material displacement and chip removalprocess during machining. Both sounds are emitted directly to theair space of the machine environment (Fig. 3).

The indirect airborne sound is induced from the impulsechanging forces, which occur during machining. These forcesinduce vibrations (waves) in a certain frequency range in the tooland in the workpiece. On the one hand, a part of the mechanicalwaves is transmitted by the tool into themachine structure. Hence,this part is insignicant due to the higher stiffness of the tool andmachine structure in relation to the stiffness of the workpiece. Onthe other hand, the changing forces induce a transversal motionand a rotational motion of each material particle of the workpiece.Due to the applied clamping method, the properties and thegeometry of the workpiece, these vibrations propagate as bendingwaves over the entire workpiece. Thereby, the propagationvelocity of the bending waves cB is a function of the bendingstiffness B0 per unit area, the site-related massm00 of the workpieceand the excitation frequency:

cB v

pB0

m004

s(1)

The structure-borne sound resulting from these waves istransmitted through the workpiece material and radiated through

through the physical system S(z) is modied by the responsecharacteristics of the control source and the workpiece between itand the error sensor. The inuence of all of these can be lumped intoa single secondary path transfer function S0(z) which is constructedthrough a preliminary system identication [4]. As illustrated inFig. 6 the error signal e(n) measured by the error sensor is a mixtureof signals from P(z) and S(z). P(z) is the primary path from the

Fig. 5. Multi-body model of the adaptronic clamping system.

J. Hesselbach et al. / CIRP Annals - Manufacturing Technology 59 (2010) 395398 397the workpiece surface into the air space of the machineenvironment (Fig. 3). To nd out if the dominant acoustic sourceis located in the area of the tooth contact or in the area of theworkpiece surface, several measurements and analyses were donewith an acoustic camera, a measurement system which usesbeamforming as signal processing technique to visually localizeacoustic emission. The image sequences in Fig. 4 show the locationof the maximum sound radiation during idling and materialremoval.

During idle running, the acoustic emission is generated mostlyfrom the tool rotation. The location of the dominant acousticemission changes instantly after the tool gets in contact with theworkpiece. The dominant noise emission moves in the middle ofthe workpiece and above. These measurements demonstrate thatthe dominant noise emission during milling on woodworkingmachining centers is generatedmainly from theworkpiece and notonly from the tool or tooth contact.

4. Mechanical and control design

To reduce the vibration and the structure-borne sound of theworkpiece, an adaptronic clamping system which is composed offour sensors, a workpiece clamped on four suction blocks and fouractuators within each of these suction blocks was developed. Thedesign and behavior of the systemwere rstmodeled and analyzedin a multi-body-simulation environment. In the simulation modelthe workpiece was displayed as a nite element model. The forceacting on the workpiece was modeled as input vector at the

Fig. 3. Direct and indirect airborne sound.workpiece edges. Likewise, each piezoelectric actuator wasmodeled as a spring-damper element and a translational joint(Fig. 5). The connection between these joints and the exible

Fig. 4. Localization of acoustic emission durmodel of the workpiece was done over additional nite elementsand interface points. The simulation results of the structurebehavior at the sensors reveal that with this actuator congurationthe vibration amplitudes of the workpiece at 300 Hz can bereduced about 14 times. Based on this result four active suctionblocks were designed. Due to the available design space eachpiezoelectric actuator was placed in horizontal position and itsactuating movement is later on translated into a vertical one(Fig. 7). A multiple-input multiple-output (MIMO) system waschosen [4] as control technique. Using a Filtered-X LMS (LeastMean Square) and/or RLS (Recursive Least Square) algorithm thecontrol system is intended to be adaptive in order to cope withvarious machining parameters and workpiece dimensions (Fig. 6).

Each control signal from a single actuator which propagates

Fig. 6. Block diagram of Filtered-X LMS algorithm using RLS cancellation pathmodeling.reference signal depending on the rotating frequency of the millingtool to the error sensor, whereas S(z) is the single secondary pathbetween each piezoelectric actuator and each error sensor.

ing idling (left) and machining (right).

its ve harmonics at 600 Hz, 900 Hz, 1200 Hz, 1500 Hz and 1800 Hz.The active clamping system was also investigated with the aim toreduce the noise levels at these frequencies by employing anaccelerometer in the middle of the workpiece surface as an errorsensor. Actuator 1 and actuator 2 controlled the frequencies of300 Hz and 600 Hz, whereas actuator 3 and actuator 4 handled thefrequencies of 900 Hz and 1200 Hz, respectively. With this cong-urationamaximalnoise level reductionat300 Hzby20 dB(A)andanoverall noise level reduction of 4 dB(A) was achieved (Fig. 9).

6. Conclusions

The vibration and noise analysis presented in this paper provethat during milling of composite boards on woodworkingmachining centers the workpiece is excited with forced impulsevibrations. These lead to high vibration amplitudes and noiseradiation of the workpiece. With regard to the analyzed results, anadaptronic clamping system based on piezo-stack actuators wasdesigned and integrated into the machine table. The experimentalresults verify that by the usage of such a system an active noise andvibration reduction can be successfully realized.

J. Hesselbach et al. / CIRP Annals - Manufacturing Technology 59 (2010) 395398398Assuming thatW(z) is a FIR- (nite impulse response) lter of tap-weight length N, the control signal y(n) is computed as

yn wTnxn (2)

w w0n;w1n; :::wN1nT (3)is a tap-weight vector and

xn xn; xn 1; :::xn N 1T (4)is an N-sample reference signal vector. The tap-weights of theadaptive lter W(z) are updated using the LMS algorithm

wn 1 wn mx0nen (5)wherem is the corresponding step-size parameter and x0(n) is anN-sample ltered reference signal. The ltered reference signal x0(n)is an approximation result after the inuence factors of thecancellation path described as follows:

x0n S0zxn (6)where S

0z is transferred from the RLS cancellation path modelingS0(z). Due to the higher stability and less computation time the LMSalgorithm is used in the control process. The identication processis left to the RLS algorithm. This algorithm identies the secondarypath faster and more precisely. This combination leads to theFiltered-X LMS controller with the RLS identication, shortened tothe FXLMS-RLS.

5. System integration and experimental results

In order to examine the practical issues associated with theMIMO-FXLMS-RLS controller, several experiments during machin-ing were carried out. Fig. 7 shows the experimental setup with theMIMO-FXLMS-RLS structure using four laser triangulation sensors(LTS) as error sensors.

The actuators and the sensors were located relatively close tothe disturbance source at the milling position, yet the machiningshould not be disturbed. The workpiece (MDF, 600 mm 600 mm 18 mm) was clamped on the active suction blocks. It was milledat a workpiece edge with a cutting depth of 2 mm and a rotationspeed of the tool of 18,000 rpm.

During the milling process, the vibration amplitude of the

Fig. 7. Experimental setup.workpiece was dominated at a rotational frequency of the tool of300 Hz. Therefore, the error signals were ltered by a narrow band-passlter in the corresponding frequency. Each secondarypath fromeachactuator to every error sensorwas identiedat the frequencyof300 Hz as well. Since an improved workpiece quality is the primaryresearch goal, the vibration amplitudes of the workpiece at themilling position (LTS 1 and LTS 2) become a priority to be reduced. Amaximum vibration reduction was achieved by 20 dB at LTS 1 and25 dB at LTS 2 (Fig. 8). At the same time, the vibration amplitude atsensors LTS 3 and LTS 4 were reduced.

Furthermore, in order to capture the noise radiation during themachining a microphone was subsequently positioned over theworkpiece surface. The dominant sound pressure levels weremeasured likewise at the tools rotation frequency of 300 Hz andFig. 8. Vibration reduction during milling process of MDF.

Fig. 9. Waterfall diagram of noise level reduction during milling process.Acknowledgements

The presented work was funded by the German ResearchFoundation (DFG), within the Priority Program 1156. The authorswould like to thank for this support.

References

[1] Directive 2003/10/EC. Ofcial Journal of the European Union .[2] Janocha H (1999) Adaptronics and Smart Structures. Springer, Berlin.[3] Neugebauer R, Denkena B,Wegener K (2007)Mechatronic Systems for Machine

Tools. Annals of the CIRP 56(2):657686.[4] Hansen CH, Snyder SD (1997) Active Control of Noise and Vibration. E & FN Spon,

London.

Development of an active clamping system for noise and vibration reductionIntroductionVibrations on woodworking machining centersNoise emission on woodworking machining centersMechanical and control designSystem integration and experimental resultsConclusionsAcknowledgementsReferences