thermal robotic arm controlled spraying (tracs)

Control 2004, University of Bath, UK, September 2004

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THERMAL ROBOTIC ARM CONTROLLED SPRAYING (TRACS) D. Breen, E. Coyle and D. M. Kennedy Faculty of Engineering Dublin Institute of Technology Dublin Ireland [email protected]

Keywords: Thermal spraying, Robot Feedback Control.

Abstract Design of a Thermal Robotic Arm Controlled Spraying (TRACS) system, is described. The research encompasses novel design features for a robotic arm manipulator, including continuous 3600 link rotation, together with automatic analysis of the thermal spraying process for feedback control of the robotic arm manipulator. The technical and simulation design will provide for the automatic application of advanced surface coatings to enhance wear, low friction and corrosion resistance properties to substrates via a thermal spraying process. Three key research areas in thermal spraying technology are described. These include the test rig and equipment configuration, a novel design of the robotic arm, and the system control strategy. Technical design, simulation, and control of the robot arm form the more research-intensive elements of the project. Software simulation, document and graphics production has been carried out using Matlab and Microsoft products and these are described in the paper.

1 Introduction Thermal Spraying Technology Thermal spraying involves the application of wear and corrosion resistant coatings to various substrates and has been traditionally carried out in the aerospace, power generation and petrochemical industries [1] Improvements in the technology have resulted in opening up of additional markets, in particular in the biomedical and electronic coating industries. It is further possible today to apply coatings to polymer-based materials [2] 1.1 Benefits of Thermal Spraying There are many benefits to industry from coating substrate materials. Benefits accrue from a wide choice of coatings [1] now available to improve the characteristics of particular

materials when compared to uncoated materials. Benefits such as improved wear characteristics will result in reduced maintenance and replacement costs [4]. 1.2 Thermal Spraying Systems Thermal spraying is a generic term for a range of thermal spraying technologies. There are four systems High Velocity Oxyfuel Spraying (HVOF), Plasma spraying, Arc spraying and Flame spraying. Flame spraying for example is used in the application of corrosion resistance aluminum to off-shore oilrigs [1,3]. Another example of surface coating is biocompatible hydroxylapatite coating of prostheses, which are made of materials such as titanium, this is achieved with the HVOF system. To understand the robot arm design issues concerned, it is necessary to expand on the powder flame spraying system which is used for this project 1.3 Powder Flame Spraying Powder flame spraying is the oldest thermal spraying process [1,3]. However it is a process that is still used extensively today because of the range of coating material and alloys available. The lower energies required reduce the health and safety risks although there are still serious health and safety risks associated with this flame spraying technology such as high temperatures, combustion emissions and general dust particles resulting from un deposited metal, polymer or ceramic powders. The vast majority of components are sprayed manually and the development of an automatic robot arm to carry out the thermal spraying process will reduce costs and health and safety risks. A schematic of the powder thermal-spraying process is shown in Figure 1. Fuel is fed to the nozzle, which is ignited to produce a flame. Powder coating material is fed into the nozzle where an aspirating gas expels the powder into the flame. The coating material melts in the flame, which in turn is directed at the substrate material to be coated. Automatic feeding of coating material into the flame will require consideration for the final robot arm design.

Control 2004, University of Bath, UK, September 2004 The molten material bombards the substrate and upon cooling, the coating mechanically bonds to the substrate. To minimize porosity the coating material should be directed perpendicular to the substrate. This is an important design and control feature of the robot arm. Table 1 lists the main categories of coating materials [9]. 1. 2. 3. 4. 5. 6.

pure metals alloys nitrides carbides Graphite-iCTM Polymers

Table 1: Coating Materials Table 2 lists the characteristics of the thermal flame spraying process [3].

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1.4 Coating process The coating process must occur in a very precise manor to ensure quality control. Following surface preparation, there can be up to three main stages in applying a metallic coating to a substrate and the location of the torch for each stage is an important design and control parameter. These include preheating the substrate, spraying the substrate with the coating material and finally fusing the coating to the substrate. Clearly the length of time taken for each stage is another design and control parameter, but this paper will concentrate primarily on torch location. Locations in the torch flame of the three stages described above are shown in Figure 2. This can be programmed either by open loop or by automated closed loop control. Closed loop control will feature prominently in the finalised prototype system design. Methods to measure these locations and control of the torch are discussed in section 3.

1 Particle velocity 40 m/s 2 Adhesion MPa < 80 3 Oxide Content 10 –15 % 4 Porosity 10 – 15 % 5 Deposition Rate 1-10 kg/hr 6 Typical deposit thickness 0.2 – 10 mm Table 2: Characteristics of thermal spraying Some of these characteristics will be used to determine the quality of the robot design such as porosity control. This will be a measurable quantity between manual spraying and automatic spraying. Figure 2: Torch Control Locations

2 Test Rig and Equipment 2.1 Thermal Spraying Torches A full range of powder thermal spraying equipment is available for use by the researchers of this project. Examples of some of the types of thermal spraying torches available are shown in Figures 3a and 3b. (Type 3a. is a powder fed torch together with coating material feed bottle; 3b. is a polymer fed torch).

Figure 1: Powder Thermal-Spraying Process. Figure 3a. Metal spray torch. Figure 3b. Polymer torch.

Control 2004, University of Bath, UK, September 2004 2.2 Two-axis Robot Test Rig At this early stage in the research, the design and development of a two-axis robot is underway to enable powder flame spraying in a semi-automatic environment, be carried out. A portion of the test rig, which will provide a prismatic / linear axis drive, is shown in Figure 4.

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One of the design problems was the attachment of the oxyacetylene torch hoses to the moving prismatic / linear axis. This can be solved using a spring loaded oxyacetylene hose reel mechanism, which is commercially available.

3 Design and Control of the Novel Robot Arm 3.1 3600 Continuous Joint Rotation and Kinematics

Figure 4 Prismatic Drive Unit A new phase-angle power converter and microcontroller control unit has been designed and built for this prismatic drive. This drive with the rotary drive unit which has its own dedicated power controller provides the basis for a two-axis thermal spraying robot which will be used for thermal spraying feed back control testing and analysis. This setup will provide a test rig for thermal spraying of the external surface of cylindrical objects. A plan view of the test rig layout design is shown in Figure 5. It is intended that the prismatic drive will have the thermal spray gun attached so that is can be moved up and down along a horizontal axis. The cylindrical object to be sprayed will be fixed to the rotary axis. With the new control unit this set-up will provide a reasonable degree of flexibility and thermal spraying options for cylindrical objects, in addition to enable experience be gained with automatic spraying.

Workspace analysis of robot manipulators shows that maximum workspace occurs when rotary joints have 3600 rotation. The first novel approach in the current research is in the design of a robot joint that provides not only 3600 rotation, but also continuous 3600 rotation. One serious problem with this type of joint is the cabling of equipment beyond the joint. Prior to addressing design issues it has been necessary to study a number of fundamental concepts, in particular robot kinematics and dynamics. This paper will address in particular the forward kinematic equations of a five-axis articulated robot arm with three-3600 continuous rotation joints. A corner stone in design of any robotic system is that of determining the kinematic equations required to model the robot arm. The kinematic equations describe the mathematical relationships between robot joint space and tool (in this instance, torch) space. Joint space may be angles in the case of rotary joints (drives) or distances in the case of prismatic joints (drives). Torch space specifies the torches position and orientation in the working environment. Denavit-Hartenberg (D-H) [5,6] presented a process for developing a mathematical model of robot manipulators, which relates joint space variables with torch space position and orientation. This model is unique to each and every robot, yet requiring only four kinematic parameters. These parameters are listed in Table 3. There is only one variable dependent on joint type the remaining parameters are fixed values dependent upon robot construction. The variables are joint angle for revolute joints or joint length for prismatic joints. Parameter Joint angle Joint length Link length Link twist

Symbol θ d a α

Table 3 Kinematic Parameters

Figure 5: Thermal Spraying Test Rig

Following consideration of various robot workspace envelope designs, including cartesian, cylindrical, spherical and articulated, a decision was made to utilise the articulated system, as this is a more suitable form from an anthropomorphic perspective. The D-H process [5] on a simple 6-axis articulated robot arm shown in Figure 6, produces a highly non-linear and coupled homogeneous matrix, as shown in equation 1. Unit vectors n, o and a


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provide the orientation of the torch tip in terms of base coordinates and vector p provides torch tip position in terms of base coordinates.

Yaw Pitch

nx ox ax px R

TH =

n y oy ay py

o

(1)

nz oz az pz

n

a

0 0 0 1 y0

Z0

Torch z0

p

y0

a

n

Figure 7. Five-Axis Robot Arm with 3600 Rotations o

x0

Base

x0

Base

These offsets complicate the Kinematic equations, but by way of an example the transformation matrix, developed for this robot arm, from frame 1 to 2 is given by equation (4).

A2 =

Figure 6. Six-Axis Articulated Robot Arm

cos θ 2

− sin θ 2

0

a2 cos θ 2

sin θ 2

cos θ 2

0

a2 sin θ 2

Each component of RTH is a non-linear coupled equation, an example of which is shown in equation (2)

n x = C1 (C 234 C 5 C 6 − S 234 S 6 ) − S1 S 5 C 6

( 2)

where C1 represents cosθ1.

θ 1 = a tan 2

py px

(3)

The robot design for this project will require a five-axis articulated robot arm, three for position each with continuous 3600 rotation and two for tilt and pitch. There is no added advantage in having roll for thermal spraying, and this will reduce the cost of the robot arm. However to provide continuous 3600 rotation the shoulder and elbow joints must be offset in the same direction, as shown in Figure 7.

0

1

d2

0

0

0

1

(4)

The overall transformation from base to torch tip is given by equation (5). R

An analytical solution will provide joint angles based on position and orientation data, for example, the equation for joint angle θ1 is shown in equation (3).

0

TH = A1A2A3A4A5

(5)

These equations are too large to reproduce here. The method used to obtain this multiplication was to use the Matlab symbolic toolbox. Work is ongoing to develop the inverse solution to this matrix. This will provide joint angles giving torch tip position and orientation for a particular torch trajectory. The forward kinematic equations may be used to determine other robot control equations, such as the robot’s Jacobian Matrix. In addition to kinematics the control of robot manipulators must consider robot dynamics and the development of control laws to manage those equations. However the dynamic equations of a robot manipulator are particularly complex when we are considering articulated robot manipulators because they are non-linear and highly coupled. The general dynamic model of a robot manipulator is a second order differential equation with highly non-linear and coupled parameter matrix coefficients. The matrix form of the dynamic model [7] of a robot manipulator is given in equation (6)


N j =1

+

D(i, j )θ j + C cent (i, j )θ N

2 j

C cor . (i, j , k )θ jθ k + hi + bθ i = τ i

( 6)

k = j +1

for i = 1 : N (number of actuators ) where D(i,j) is an inertia tensor matrix term, Ccent(i,j) is a centrifugal matrix term, Ccor (i,j,k) is a coriolis matrix term, hi is a gravity term, b is a friction term and τi is a torque term. A number of methods of analysis are under investigation, in particular gravity compensation techniques as gravity plays a significant part in the dynamic model of articulated robot manipulators. Due to the twisting nature of the offsets providing the 3600 robot arm capability, the friction term is also likely to play a more than normal role in the dynamic model. Speed and acceleration will not pose a significant challenge in the robot design, therefore the centripetal and coriolis forces are likely to play a somewhat less significant roll in the dynamic model of this design. 3.2 Cabling 3600 Continuous Rotation Joints

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a nickel-phosphorus matrix with particles of polytetrafluoroethylene (PTFE) uniformly distributed throughout the matrix. A key advantage of the material is, that as wear occurs new PTFE particles are exposed, maintaining a low coefficient of friction. Further research and testing of this is required, however some of its features include the following; TM 117C heat-treated 590 0F Coefficient of friction between 0.1 - 0.7 Electrical resistivity 130-200 µΩ-cm 3.3 Real-time Measurement of Surface Coating Thickness as a Robotic Arm Control Parameter Implementation of closed-loop trajectory planning and execution will require feedback control signals. An important control parameter of thermal spraying is the automatic depth measurement of the coating being applied to the substrate material. To achieve this, a low-cost light emitting diode (LED) and charged coupled device (CCD) camera combination and triangulation, is being considered. A typical construction is shown in Figure 9.

One significant problem with 3600 continuous rotation joints is the cabling of power and data along the robot arm. The Harmonic Drive and Megatorque motor have hollow shafts that allow cabling through the device, but to date do not allow continuous rotation. A solution being investigated is to make the electrical connections via slip-rings and brushes as shown in Figure 8, but omitting traditional materials such as copper for the slip rings and carbon brushes, as these materials would not be sufficiently robust.

Figure 9. Light Emitting Diode (LED) and ChargedCoupled Device (CCD) Camera Combination

Figure 8. Slip-Rings for 3600 Rotation A material with low friction, low wear and low resistivity, is required. Such material would not wear out significantly over the life of the actuator, would not introduce any significant friction and owing to its low resistivity would provide good electrical connections. Having researched available material types with the required properties, a material referred to as TM 117C [8] may be sourced and used in this application. This material is made of

Investigation of the correlation between change in depth of substrate material and movement across the CCD chip is ongoing. A single wavelength LED and matched CCD camera will be required, however interference will be significant from the thermal spray. Implementation of the Digital Signal Processing algorithms will be achieved with processors from the Texas Instruments TMS320C6000 family of DSP chips. A typical LED-CCD combination may comprise a Gallium Phosphide LED with a wavelength of 550 nm and a monochrome CCD camera with peak response in this region.

Control 2004, University of Bath, UK, September 2004 3.4 Real-time Control of Torch Perpendicularity to Substrate In order to minimize surface coating porosity, the torch must maintain a 900 angle with the substrate. To achieve this it is intended to set up an experimental system comprising two CCD cameras positioned at right angles as shown in Figure 10, enabling image processing of the edge of the torch blue cone area at the tip of the torch as shown in Figure 11. It may be possible using edge detection techniques such as Roberts, Sobel or Canny edge detection algorithms [10] to use the edges of the blue cone as control signals for maintaining the correct torch position. This area will require further research and testing.

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of feedback vision systems and allowing a greater degree of movement offers new potential for this technology. Based on the present research and investigation, a final prototype of a robot arm incorporating the design features discussed in the paper will be developed and tested in specified working environments.

References: [1]

Air Products “Thermal Spraying” (accessed 6/03) http://www.airproducts.com/Products/CylinderGases

/MAXX/ThermalSpraying/thermalspraying_techpap

er

[2]

G. England “Thermal Spray Coatings on Carbon and Glass Fiber Reinforced Polymers” (accessed 6/03) http://www.gordanengland.co.uk/frpapp

[3]

Richard Halldern “Flame Spraying” TWI (2001) http://www.twi.co.up/j32k/protected/band_3/ksrdh00

1.html Figure 10. CCTV Set-up to Check Perpendicularity

Torch head to be controlled

[4]

David M. Kennedy “Surface Engineering Addressing Maintenance Applications” DIT

[5]

Saeed B. Niku, Introduction to Robotics Analysis, Systems, Applicatiosn, pp 67-75, Prentice Hall 2001

[6]

CCD imager

Robert J. Schilling, Fundamentals of Robotics Analysis and control, pp 51-54, Prentice Hall 1990

[7]

Wesley E Snyder, Industrial Robots: Computer Interfacing and Control, pp208-209, Prentice-Hall

Substrate

[8]

Techmetals Inc. “TM 117C coating”

[9]

Teer Coatings Ltd “Coatings”

[10]

Paul F.Whelan, Derek Molloy, Machine Vision Algorithms in Java Techniques and Implementation,

Figure 11 CCTV Set-up: Image Processing of the Edge of the Torch Blue Cone Area at the Tip of the Torch

4 Conclusions The design and control of a robotic arm for depositing surface coatings onto substrates in hazardous environments has been discussed and presented. A number of novel features have been discussed which would make this robotic arm user friendly and robust. The application of robots for conducting demanding and precision type work in hazardous environments is not new but the ability of a robot system to apply surface coatings to a prescribed thickness, making use

pp 82-90 Springer 2001.